1. science
2. mathematics
3. statistics

Department of Statistics
Academic Program Review
Spring 2015
Department of Statistics • Texas A&M University • 3143 TAMU • College Station, TX 77843-3143
(979) 845-3141 • www.stat.tamu.edu
Table of Contents
I.
II.
III.
Introduction
Brief History of the Department……………………………………………………. 4
Mission and Goals………………………………………………………………….. 8
Administrative Structure of the Department………………………………………... 11
Resources…………………………………………………………………………... 13
Analysis……………………………………………………………………………. 14
Undergraduate Program……………………………………………………………. 15
Graduate Program………………………………………………………………….. 16
Professional Education……………………………………………………………... 19
Challenges and Opportunities……………………………………………………… 20
Assessment………………………………………………………………………… 22
Student Report
Graduate Program in Statistics……………………………………………………… 28
Master of Science Program…………………………………………………………. 29
Doctor of Philosophy Program……………………………………………………... 32
Internship Program…………………………………………………………………. 35
Undergraduate Course Offerings…………………………………………………… 36
Graduate Course Offerings………………………………………………………… 37
Scheduling Coursework…………………………………………………………….. 42
Graduate Program Admissions Criteria……………………………………………... 43
GRE Scores for First Time Students………………………………………………... 44
Graduate Students Applied, Admitted, and Enrolled ………………………………. 45
Students by GPR Range……………………………………………………………. 48
Institutional Support for Full Time Students……………………………………….. 50
Honors & Awards Received by Students…………………………………………… 51
Statistics Graduate Student Association…………………………………………….. 54
Student Publications………………………………………………………………... 55
Professional Development Opportunities for Students……………………………... 56
Average Year to Degree, By Degree Program………………………………………. 57
Masters Graduation and Retention Report…………………………………………. 58
Doctoral Graduation and Retention Report………………………………………... 59
Master’s Degrees Awarded…………………………………………………………. 60
Ph.D. Degrees Awarded……………………………………………………………. 65
Ph.D. Graduate Employers………………………………………………………… 69
Faculty Information
Department of Statistics Faculty……………………………………………………. 73
Average FTE for Faculty Rank……………………………………………………... 76
Faculty Rank by Ethnicity………………………………………………………….. 77
Headcount by Faculty Rank………………………………………………………... 78
Demographics by Faculty Rank…………………………………………………….. 79
Honors and Awards Received by Faculty…………………………………………... 80
Committee Assignments……………………………………………………………. 81
Faculty Editorial Service……………………………………………………………. 82
1
IV.
Primary Investigator Awards……………………………………………………….. 85
Co-Principal and Collaborating Investigator Awards……………………………….. 88
Faculty Collaborations within Texas A&M…………………………………………. 90
SCH per FTE and Student/Faculty Ratio………………………………………….. 93
Faculty Summary…………………………………………………………………… 94
Weighted Average Faculty Salary Comparisons……………………………………... 95
Goldplate Funding………………………………………………………………….. 96
Semester Credit Hours Taught by Faculty Rank…………………………………….. 97
History of Courses Taught………………………………………………………….. 102
Appendix
A.
MS Statistics and Online Programs…………………………………………. 105
B.
MS Analytics Overview……………………………………………………... 111
C.
Proposal for an Undergraduate Major in Statistics………………………….. 115
D.
Postdoctoral Training Program in Biostatistics, Bioinformatics
and the Biological Basis of Nutrition and Cancer…………………………… 122
E.
Institute for Applied Mathematics and Computational Science……………... 124
F.
Center for Statistical Bioinformatics………………………………………... 128
G.
Statistics Gifts and Endowments…………………………………………… 129
H.
Colloquium and Seminar Speakers………………………………………….. 130
I.
Department of Statistics Alumni Advisory Board…………………………… 142
J.
Faculty Postdoctoral Researchers…………………………………………… 200
K.
Department Bylaws………………………………………………………… 202
L.
Faculty Biographical Sketches………………………………………………. 217
2
I.
INTRODUCTION
3
Brief History of the Department
The Department of Statistics was formed in 1962 as the Graduate Institute of Statistics with the
mandate of providing statistical research, consulting, and instruction for Texas A&M University. The
Department was authorized from its inception to grant MS and PhD degrees. Prior to 1962, a number of
different departments provided the few statistics courses taught at the undergraduate and graduate level. H.O.
Hartley was the Institute's first Director and by the fall of 1964 the Department consisted of a faculty of five
with twelve graduate students.
The Department resided in several locations prior to its moving to the Olin E. Teague Building in
1966. The construction of this building was greatly assisted by an NSF Center for Excellence grant obtained
by Professor Hartley and others. The university’s computing center also resided in the Teague Building. The
rapid expansion of the university during the 1970s and subsequent demands for space by the computing center
resulted in the Institute moving to its current location on the fourth floor of the John R. Blocker Building in
1981. In the fall of 2004, the Department acquired additional office space on the fifth floor of the Blocker
Building.
The Graduate Institute of Statistics was included in 1966 as a member of the newly formed College
of Science and in 1984 acquired its current name, the Department of Statistics. In 1977, Dr. Hartley retired
and was succeeded by Dr. William B. Smith. By the early 1980s the Department had grown to 18 faculty
members with 40-50 graduate students. The next two department heads were Dr. Raymond J. Carroll,
appointed in 1986, and Dr. H. Joseph Newton in 1990. The faculty by this time had grown to 25 members
with 60-65 graduate students. Along with this increase in the size of the faculty and graduate student
population was a concurrent increase in research productivity and funded research. Another indicator of the
university's high regard for the Department was the designation of Drs. Manny Parzen and Raymond J. Carroll
as Distinguished Professors. At the time, there were only 46 faculty members currently holding the title of
Distinguished Professor at Texas A&M University.
In 1998, Dr. James Calvin was appointed to head the Department, which, at that time, consisted of
26 faculty members with 60-65 graduate students. Dr. Calvin served as Department Head for 6 years.
With the appointment of Dr. Simon Sheather in March 2005 as Department Head, the department
embarked on two major initiatives in the area of online teaching. In 2006, the Texas A&M University System
Board of Regents approved the introduction of the Master of Science degree in Statistics for distance delivery.
The first cohort of 20 students started the program in Fall 2007. By the Spring 2014 semester there were over
400 students enrolled in on-line statistics graduate courses, with 292 seeking an M.S. degree. Over 100
4
students have completed the program and received their M.S. degree in Statistics. The distance master’s is a
key source of revenue for the Department, and arguably the most successful statistics distance-learning
program in the nation. Further details regarding the distance learning masters program is provided in
Appendix A. In 2012, a second distance-learning program was initiated when an agreement was reached with
the Mays Business School to offer a joint MS Analytics program; this program began in Fall 2013. The
Analytics program has experienced great initial success, and in the Fall of 2014 28 students enrolled in the
program. The first cohort of students is expected to graduate in May 2015. Further details regarding the MS
Analytics program is provided in Appendix B. In addition to the distance M.S. programs in Statistics and
Analytics, a “fast track” PhD program was introduced in 2008, and a Certificate of Applied Statistics was
approved. In 2009, a joint TAMU/SAS certificate was introduced and the number of supported on-campus
graduate students was expanded with the introduction of Technology Teaching Assistants. The Department
also added two more Distinguished Professors, Drs. Clifford Spiegelman and Bani Mallick.
A history of the Department was published on its 50th anniversary in 2012, 1 and the anniversary was
celebrated the following year in March. A short video prepared for this gathering is available on line at
https://www.youtube.com/watch?v=A9v2dZ5C5Ei.
In March of 2014, Dr. Valen Johnson was appointed as Department Head. Dr. Johnson was recruited
to the Department in 2012 as one of three faculty hires supported by the Applied Mathematical, Statistical
and Computational Sciences (AMSCS) white paper, which had been selected as a research landmark area in
2009.
From its inception, the Department has been substantially involved in collaborative research. Dr.
Hartley and the faculty had research grants and contracts from ONR, NASA, Army Research Office, and
National Center for Toxicological Research. For over twenty years, the Texas Agricultural Experiment Station
provided funding for statistical consulting. The Department was actively involved in the development of the
Center for Environmental and Rural Health, an NIEHS funded research center. Also, several faculty members
greatly assisted in obtaining the competitive renewal of Texas A&M University's EPA funded Superfund Basic
Research Program. In 2001, Professor Carroll received a grant from NCI to establish a two-year training
program in Bioinformatics. The success of this program has resulted in the grant being renewed through 2016.
A number of faculty have also been appointed as adjunct faculty at M.D. Anderson Cancer Center (MDACC),
1
S. Sheather and J. South, Texas A&M Department of Statistics, Strength in Numbers: The Rising of Academic
Statistics Departments in the U.S., eds A. Agresti and X.-L. Meng, Springer, New York (2012).
5
and several students and post-doctoral researchers are currently jointly supported by MDACC and
Departmental faculty.
The Department has established four major lecture and award series. The H. O. Hartley Memorial
Lecture series was established in 1988 to honor the memory of Herman Otto Hartley. Past speakers include
Peter J. Diggle, Bradley Efron, E.J. Hannan, Sir David R. Cox, Wayne Fuller, Adrian Raftery, Peter Hall, Terry
Speed, James Berger, Edward George, Regina Liu, and David Dunson. The Parzen Prize for Statistical
Innovation was established in 1994. Past awardees include Grace Wahba, Donald P. Rubin, Bradley Efron, C.
R. Rao, David R. Brillinger, Jerome H. Friedman, Alan E. Gelfand, Nancy Reid, Marvin Zelen, Roger
Koenker, Adrian Raftery, and Trevor Hastie. The Department established the third lectureship, the Ronald
R. Hocking Lecture Series, in 2002 to recognize exceptional contributions to the field of linear models and
their generalizations. Past speakers include Ronald Hocking, David Harville, Dallas Johnson, Ramon Littell,
Michael Kutner, Tim Hesterberg, Brian Marx, Oliver Schabenberger, John Sall, Garrett Fitzmaurice, and
Goutam Chakraborty. In 2009 the fourth award and lecture series, the Raymond J. Carroll Young Investigator
Award, was inaugurated. This award is bestowed in alternate years on a junior investigator who has made
outstanding contributions in the area of statistics. Past recipients include Samuel Kou, Marc Suchard, and
Tyler J. VanderWeele. All four of these lecture/award series have provided the Department’s graduate
students with the opportunity to interact with pioneers in the statistics profession.
The Department also presents several prestigious internal awards to outstanding former and current
students.
Among these is the Margaret Sheather Memorial Award in Statistics, which was awarded from
2010-2014 and was presented annually to the student(s) with the most outstanding master’s project(s). In
2015 this award was re-established as the Margaret Sheather Memorial Award in Analytics and in the future it
will be awarded to the MS Analytics student(s) with the most outstanding capstone project(s). The Hartley
Award is presented annually to a former student for distinguished service to the discipline of statistics. The
William S. Connor Award is presented annually to the student whom the faculty deems most outstanding
amongst those students passing the preliminary examination during the current year. A description of funds
raised to support these awards, as well as the lecture series above, is provided in Appendix G.
The Department’s students frequently also attract external awards. Notable among these are the
success of our graduate students in recent Capital One Statistical Modeling Competitions. The Department
fielded the winning team and a finalist team in 2012, another finalist team in 2013, and the winning and a
finalist team in 2014. A list of these awards and other student honors appears on page 51.
The Department does not currently offer an undergraduate degree in statistics.
However,
undergraduates can obtain a concentration in statistics, and the Department developed, in conjunction with
6
the Mathematics Department, a statistics option within the BS degree in Applied Mathematical Sciences. The
Department also offers a minor in statistics. The Department's undergraduate course offering has grown to
over ten courses with approximately 5,700 undergraduates enrolled per academic year. Besides the courses
offered to its MS and PhD students, the graduate service courses have an enrollment of over 1,500 students
per academic year.
For many years, the Department hosted a Statistics Advanced Placement Summer Institute on-campus
for high school mathematics teachers, and, thanks to the dedication of our Emeritus Professor James Matis,
will begin doing so again this summer. This institute provides an opportunity for the Department to interact
with AP statistics teachers, and it is our hope that this interaction will serve as a mechanism for advertising
the Department’s role in undergraduate statistics education to high school students across the state.
In 2012, members of the Department formed Texas A&M Statistical Services, LP, an external
consulting center that provides 99% of its profit to Texas A&M University. Drs. Simon Sheather and Edward
Jones serve as President and Executive Vice President of this limited partnership.
After a period of sustained growth in the number of faculty, from 5 full-time tenure-track faculty
members in 1964 to 26 tenure-track faculty members in 2000, the growth in the number of tenure-track faculty
has ebbed and flowed since the turn of the century, this despite the dramatic increase in the number of
students taking, or wanting to take, statistics courses. The problem has been partially offset by the addition
of a highly qualified group of senior lecturers, which is supported from soft money resources. This problem
is discussed further in the Challenges and Opportunities Section below, but it is clear that the Department has
a pressing need to expand its course offerings to meet the increasing demand for statistics courses in the era
of “Big Data.” This need can only be satisfied with an increase in the size of its faculty.
7
Mission and Goals
Statistical science is a broad discipline that encompasses activities from data acquisition and
processing, exploratory data analysis, complex modeling of stochastic processes, inference, hypothesis testing,
parameter estimation, uncertainty quantification, casual inference, and decision making under uncertainty.
The Department’s mission is to function as a leading international center for statistical research, education
and service.
Faculty members in the Department contribute to a broad spectrum of research in statistical
methodology and application, and faculty in the department have received numerous national and
international awards for their contributions to statistics. Faculty members in the Department have received
the COPPS Award (Carroll), Noether Senior Scholar Award and Lecture (Carroll, Spiegelman), and the
Wilcoxon Prize (Carroll). (A more complete listing of faculty awards is provided in on page 80).
Current strengths of Department include spatial statistics, Bayesian methodology, functional data
analysis, modeling of measurement error, non-parametric methods, and analysis of high and ultra-high
dimensional data. Further discussion of the faculty’s research productivity is provided in the Analysis section
below.
As part of a land-grant university, the Department takes its responsibility for statistical education very
seriously. The Department teaches approximately 5,700 undergraduate students each year. A vast majority
of these students enroll in service courses designed to provide a rudimentary understanding of statistics that
will allow them to interpret scientific findings in their fields of study, as well as to interpret statistical analysis
reported in popular media, government studies and business reports. The more advanced of these courses
also provide students with background in experimental design, the statistical analysis of simple experiments
and observational studies, and regression analysis.
In addition to undergraduate service courses, the Department also teaches approximately 1,500
graduate-level students from other departments.
Many of these students come from the College of
Engineering, but it is common for graduate students from across the university to enroll in the Department’s
graduate course offerings to satisfy requirements in their degree programs.
A major extension of the Department’s educational mission has been to provide Texas (as well as
other U.S. and foreign) students with an opportunity to obtain graduate training remotely through our distance
learning program in statistics. The TAMU distance master’s program is one of the largest programs in the
nation, having conferred over 100 master’s degrees to program participants since its beginning in 2007. A
similar extension of the Department’s educational mission began in 2012 with the start of the Master of
8
Science degree in Analytics. This program will likely soon enroll approximately 50 students each year into the
rapidly expanding field of applied statistics.
Faculty members in the department also play a major role in service to the University, to the
international statistics community, and to the broader general scientific community. During the last three
years, faculty members in the Department have served as editors or co-editors of three statistical journals:
Chemometrics & Intelligent Laboratory Systems, Journal of Nonparametric Statistics, and Bayesian Analysis. In addition,
they have filled 25 associate editor positions for numerous other journals, including the American Statistician,
Biostatistics, Chemometrics & Intelligent Laboratory Systems, Electronic Journal of Statistics, Journal of Biometrics &
Biostatistics, Journal of Business and Economics, Journal of the American Statistical Association: Applications & Case Studies,
Journal of the American Statistical Association: Theory & Methods, Journal of Computational and Graphical Statistics, Journal
of Nonparametric Statistics, Journal of Transportation and Statistics, SIAM Journal of Uncertainty Quantification, STAT,
Statistics, and Statistics & Probability Letters. A detailed listing of editorial service provided by Departmental
faculty is provided on page 82.
The Departmental faculty are also actively engaged in service to the University, and have been
instrumental in influencing its direction on both administrative and scientific matters. At the College level,
faculty members have served on the Faculty Advisory Committee, the Diversity Committee, and the Dean
Search Committee.
At the University level, Departmental faculty members have served on dozens of policy making
committees and bodies, including the Association of Former Students’ College-Level Teaching Awards
Member Selection Committee; Core Curriculum Technology Enhanced Grant Committee; Department
Heads Council; Distinguished Award Committee; Email Selection Advisory Committee; External Advisory
Board for AgriLife Genomics and Bioinformatics Services (TAGS) Core; Faculty Senate; Faculty Senate
College of Science Caucus; Massive Open On-line Course Exploration Committee; Massive Open On-line
Course Advisory Committee; President’s Council on Climate and Diversity; President’s Task Force for Faculty
Evaluations; Price, Waterhouse & Coopers Advisory Committee; Strategic Planning Committee Strategic Reallocation Sub-council; Undergraduate Academic Appeals Panel; and the Workplace, Climate & Diversity
Committee.
In service outside of the University, faculty members have played a significant role in setting national
science policy and participating in the governance of major scientific organizations. For instance, faculty
members in the Department have served on the National Academy of Science Strategic Highway Research
Program and the Board of Trustees for the National Institute of Statistical Standards. They have also assisted
in the governance of the American Statistical Association (ASA), the nation’s largest organization devoted to
9
statistical science. During the last three years, faculty have served on the ASA’s Noether Senior Scholar Award
and Noether Young Scholar Award Committees and have been elected as members of the ASA Section on
Statistical Consulting. They have served on the Steering Committee for the ASA Conference on Statistical
Practice, have co-chaired the ASA Committee on Membership and Retention, and have served on both the
ASA Task Force on Membership Growth and as the ASA representative to the AAAS. Faculty members
have also served on NSF and NIH review panels.
10
Administrative Structure of the Department
The graphic below depicts the organizational chart for the Department. Duties and responsibilities
for faculty members in the department, and in particular for faculty holding administrative positions in the
Department, are described in the Faculty Bylaws, which were adopted in the spring of 2015 and appear in
Appendix J. Noteworthy features of the chart include the MS Analytics and Online Program, as well as the
lack of an Undergraduate Advisor.
As discussed below, the Department is currently in the process of creating an undergraduate degree
program in statistics. We anticipate that this degree will begin in the Fall of 2016. An Undergraduate Advisor
will be appointed in the Fall of 2015 when this program is approved at the university level.
The MS Analytics and Online Program manages the distance learning master’s degree program and
the newly instituted MS Analytics program. The Academic Director of the Program is Dr. Simon Sheather,
and salaries of the Program staff are paid from the revenue that the Program generates. The program also
provides partial salary support for Nathan Segrest, who assists with the program’s IT structure, as well as
providing partial support for Technical Teaching Assistants (TTAs), who support the distance learning and
analytics programs.
In addition to the administrative structure depicted in the organizational chart, the Department also
hosts the Center for Statistical Bioinformatics and the Institute for Applied Mathematics and Computational
Science (IAMCS). It also sponsors a training program in bioinformatics and nutrition. The entities are
described in Appendices D-F.
11
Professor and Head
Valen Johnson
Department of Statistics
Assistant to
Department Head
Kristen Vodak
Organizational Chart
March 2015
Graduate Advisor
Jianhua Huang
Administrative
Assistant
Elaine James
Professor and Associate
Department Head
Michael Longnecker
Distinguished Professors
Raymond J. Carroll
Bani Mallick
Clifford Spiegelman
Academic Director of
MS Analytics & Online Programs
Simon Sheather
Assistant to the
Director
Jennifer South
Professors
Associate Professors
Senior Lecturers
Willa Chen
Daren Cline
P. Fred Dahm
Jeffrey Hart
Ursula Müller-Harknett
H. Joseph Newton
Mohsen Pourahmadi
Michael Sherman
Suojin Wang
Thomas Wehrly
Alan Dabney
Mikyoung Jun
Huiyan Sang
Samiran Sinha
Suhasini Subba Rao
Lan Zhou
Derya Akleman
Julie Carroll
Elizabeth Kolodziej
Hwa Chi Liang
Henrik Schmiediche
Keith Hatfield*
*Promotion effective 9/1/15
Anirban Bhattacharya
Matthias Katzfuss
James Long
Houssein Assaad (RJC)
Irma Hernandez-Magallanes (RJC)
Mathew McLean (RJC)
Daniel Mohsenizadeh (RJC)
Roger Zoh (RJC)
Katherine Reed (VJ)
Ardala Breda Andrade (VJ)
Nilotpal Sanyal (VJ)
Ayako Yajima (VJ)
Xuedong Pan (VJ)
Program Manager - Analytics
Javier Aldape
Director of Operations
Kim Ritchie
Assistant Professors
Post Docs/Researchers
Director - Analytics
Myra Gonzalez
Director of Information
Technology
Henrik Schmiediche
Sr. Microcomputer LAN
Specialist
Steve Shoemake
Nathan Segrest
Executive Professor
Edward Jones
Program Manager - Online
Penny Jackson
Business Coordinator
Wanda Ransome
Administrative Assistant
Nicole Padilla
Business Administrator
Sandra Wood
Office Software Associate
Andrew Moua
Business Coordinator II
Athena Robinson
Program Manager and
Assistant to Raymond Carroll
Joyce Sutherland
Graduate Advisor II
Amy Parker
Computer Technician
Nathan Segrest
12
Resources
The physical home for the Department of Statistics is the Blocker Building, dedicated in 1983 and named in
honor of John R. Blocker, a member of the class of ‘45 and former member of the Texas A&M University System
Board of Regents. The Blocker building is a workhorse for teaching and study at Texas A&M University with its
numerous lecture halls, classrooms and labs. In addition to housing the Department of Statistics, it is also home to a
computer lab for general use by all A&M students, the Department of Mathematics, Health and Kinesiology, and the
Dean’s Office for the College of Science. The Department of Statistics occupies the entire fourth floor, which
contains 25,000 square feet divided into 105 offices used by faculty, visitors, lecturers, post docs, graduate students
and staff. In addition, the department controls five conference and/or meeting rooms, three class and/or seminar
rooms and a server room.
The Department of Statistics operates a hybrid-computing environment of over 300 Windows, Mac and Linux
systems to meet the computing needs of its faculty and students. The Department controls much of its own
computing infrastructure and employs three full time IT professionals to oversee operations. Faculty have regular and
recurring access to computing funds, ensuring their personal systems are up to date. A partial list of statistics software
available includes Matlab, R, Stata, SAS, JMP and high performance commercial compilers. For computationally
intensive research, the department operates a 20-node / 500 core Linux cluster. For teaching, it operates three
computing labs with approximately 50 computers in each. Exclusive access and control of these resources enables the
cluster and labs to be configured and tuned for statistics faculty research and teaching requirements.
Texas A&M University operates multiple research computing clusters to which faculty have access. These
include: “Ada,” a 845 node / 16900 core x86 cluster with a peak performance of 337 TFlops, 4PB storage and FDR
network fabric; “Neumann,” a 2048 node / 32768 core Blue Gene Q cluster with a peak performance of 419 TFlops
and 2PB of storage; “Eos,” a 412 node / 3552 core x86 cluster, 500TB storage and a QDR Infiniband fabric; “Brazos,”
a 300 node / 3000 core x86 cluster, 200 TB storage and DDR Infiniband fabric. Several of these clusters contain
special compute nodes with up to 2TB of RAM or with GPU equipped nodes. Two smaller Power P7+ clusters with
23 and 49 nodes are available as well. The aggregate peak performance of these computing resources is over 800
TFlops with more than 6PB of storage.
13
Analysis
The preeminent goal of the Department of Statistics is to establish itself as an international center for statistical
research, education and service. In many ways, the department has achieved this goal: It is currently ranked among
the top 15 statistics departments in the nation by US News and World Report (sixth among public institutions), and
has been ranked as high as 11 (2010). Of course, it would be a mistake for the department to assess its success based
entirely on such rankings, although it is necessary for the Department to establish goals and a set of metrics to be
used in evaluating its progress toward achieving these goals. In this regard, the imperatives and metrics established
by the University in assessing Vision 2020 goals are useful, as many of these imperatives and metrics are highly
correlated with external rankings of the Department by entities like US News and World Report. They also coincide
well with the goals that the Department has set for itself.
Four of the twelve imperatives in the University’s Vision 2020 focus on enhancing the undergraduate
experience, building the letters, arts & sciences core, strengthening the graduate program, and building on the tradition
of professional education.
The key metrics that are being applied by the University to the Department to assess progress toward achieving
the Vision 2020 goals involve the following outcomes:
-
Publications by faculty
Citations of faculty publications
Grant funding attracted by faculty
Honors and awards
Master’s of Science two-year graduation rates
Doctoral five-year graduation rates
Before discussing assessment criteria and how the Department has performed according to them, it is useful
to first discuss the major initiatives that the Department is undertaking and how they support the four Vision 2020
imperatives listed above.
14
Undergraduate Program
Beginning in the fall of 2014, the Department’s faculty endorsed several proposals to develop an
undergraduate Bachelor of Science degree program in Statistics. Over the course of the next several months, the
faculty (notably Drs. Dabny and Wehrly and other members of the Undergraduate Committee) developed and
submitted a completed proposal to the College of Science (February 2015). This proposal is now working its way
through administrative channels, and it is expected that the program will begin in the fall semester of 2016.
The undergraduate degree program will benefit the Department and University in numerous ways. First and
most obviously, it will provide Texas A&M University undergraduates with an opportunity to obtain a highly
marketable degree in arguably the most interesting of all fields of study. Studies that attest to the marketability of
statistics degrees abound and are described more fully in Appendx C. For convenience we repeat here two typical
conclusions cited in that appendix:
According to the National Center for Education Statistics (NCES) Digest of Education Statistics (DES), the number of
Bachelor of Science degrees in statistics increased 40% from 2009 to 2011, 78% from 2003 to 2011, 26% from 2011
to 2012, and 20% from 2012 to 2013.
According to the Bureau of Labor Statistics, there were 24,950 workers classified as statisticians in 2013. This
represents a 21% increase in the five years since 2008. The field was projected to grow by a further 27% (classified by
BLS as “much faster than average”) during 2012 – 2022.
In terms of Vision 2020 imperatives, the addition of an undergraduate statistics program will enhance the
undergraduate experience at Texas A&M University, and it will substantially strengthen the University’s science core.
The addition of this major will also have numerous benefits for the department. As the number of majors in the
program grows, additional faculty lines will be provided to the Department (one new faculty line per 50 undergraduate
majors). The addition of the major will also provide faculty with greater opportunity to teach advanced undergraduate
courses in statistics. A subset of these advanced undergraduate offerings will be made available to our distancelearning master’s students, which will provide them with more elective opportunities to satisfy their degree
requirements. Finally, the addition of an undergraduate major will enhance the reputation of the Department both
within and outside of the University.
A major impediment that the Department faces in establishing the undergraduate degree is its lack
of control over a large classroom. This prevents the department from teaching large service courses in one
or two sections, instead requiring it to devote substantial resources to teach these courses in multiple smaller
sections. As the Department develops its undergraduate major, access to large classrooms in which to teach
service courses will be essential if the Department is to broaden its offering of more advanced undergraduate
courses in statistics.
15
Graduate Program
The Department is also striving to enhance the quality of its graduate program. Since the last Academic
program review, the department has undergone two major reviews of the graduate program, with the second still
underway. In 2008, the Department restructured its graduate program and separated the qualifying exams for MS
students and Ph.D. students. Prior to 2008, MS students and Ph.D. students took the same courses during the first
year in the graduate program and took the same qualifying exam in August of their second year. This arrangement
delayed the progress of students who entered the program with strong background in statistics. To address this
problem, a fast Ph.D. track was created to allow students with strong background to advance more rapidly to the
completion of their degree. This structural change also played an important role in maintaining a distinction between
doctoral and master’s level courses as enrollments in the distance-learning master’s program skyrocketed.
The 2008 restructuring also established a core curriculum for the Ph.D. program that consisted of seven
courses: Probability Theory (STAT 614), Asymptotic Statistics (STAT 620), Linear Models (STAT 612), Methodology
I (STAT 613), Applied Statistics and Data Analysis (STAT648), Computational Statistics (STAT 605), and
Methodology II: Bayesian Statistics (STAT 632). Students were required to take three qualifying exams from the first
six courses listed in this core, with two courses forming the basis for each exam. That is, the Theory Exam covered
material taken from STAT 614 and 620; the Methodology Exam covered material taken from STAT 612 and 613; and
the Applied and Computational Exam covered material from STAT 648 and 605. Students who passed two of the
three exams were advanced to Ph.D. candidacy. Students were given two chances to pass the qualifying exams.
The 2008 restructuring of the graduate program alleviated a number of problems associated with the program,
perhaps most importantly by creating a mix of classes that were appropriate for presentation to students at either the
master’s or doctoral level. It also provided for a more rapid route for incoming students with strong backgrounds in
mathematics or mathematical statistics to move beyond the qualifying exam and begin thesis research.
The revised structure of the program did not resolve a number of other existing problems, however. As
implemented, the program created a barrier that prevented students who had failed the doctoral exam from quickly
completing a master’s degree. Part of this problem stemmed from the fact that the courses required for the doctoral
degree were different from those required for the master’s degree. Students who failed the doctoral qualifying exam
often needed to take additional courses to obtain a master’s degree, despite the large overlap in material covered in
some master’s and doctoral courses, with material covered in the doctoral courses being taught at a higher level. In
addition, separate qualifying exams were administered to doctoral and master’s students, and there was no mechanism
for students who failed the Ph.D. qualifying exam to be given a pass on the master exam without sitting for the
master’s exam at a later date. Finally, by requiring students to pass only two of three qualifying exams, and giving
students the option to take the examination twice, many students did not pass (or fail) the qualifying exam until August
of their third year in the program. Students who failed the exam in their third year were then provided with up to
16
four years of funding to complete a master’s degree. These problems have hindered the Department’s effort to meet
Vision 2020 goals of graduating 75% of MS students in two years, and 50% of PhD students in five years.
To address these problems, Dr. Jianhua Huang, Graduate Advisor, and other members of the Graduate
Committee began another review of the graduate program in the summer of 2014. That review is ongoing, but
changes made to the program as a result of this review currently include the following:
-
-
-
-
The department’s course list was revised to clearly identify the levels at which statistics graduate courses are
taught (MS versus PhD), with a stipulation that MS level courses do not satisfy certain PhD level course
requirements.
Upon approval of the Associate Department Head, students in the master’s program are permitted to
substitute PhD courses toward their degree requirements.
All students can take the PhD qualifying exam in lieu of the MS qualifying exam; outcomes of PhD qualifying
exam were modified to include PhD pass, MS pass, fail, and pass at either level contingent on further course
work.
All PhD students are required to take at least 5 PhD level electives.
All PhD students are required to take 2 credits of statistical consulting (STAT 684)
Core PhD courses are evaluated using the following criteria:
o “A” represents PhD level work
o “B” represents MS level work
o “C” represents work not at graduate level
The written Ph.D. qualifying exam will be offered in May, two weeks after the spring semester final exams.
Course grades and exam grades are both considered in evaluating the outcome of the doctoral qualifying
exam.
Students with strong incoming background can take the doctoral exam after first year of courses; all other
students take the exam after their second year. The PhD qualifying examination can be taken only once.
Students must pass a Preliminary Examination administered by the student’s advisory committee within three
semesters after passing the PhD qualifying exam.
The presentation of PhD dissertation research will be open to the public.
In addition to these changes to the program, the Department’s review of its graduate program is continuing,
and additional changes are expected after faculty discussion during the spring and summer of 2015. Particular items
on the agenda include the following:
-
-
Strengthen international collaborations with universities to (a) improve the visibility of the department, (b)
help recruit outstanding graduate students, and (c) gain leverage in funding graduate students.
Enhance and standardize the departmental student award system. Create new awards for outstanding course
work and outstanding research. Standardize the procedures for providing support for students to travel to
conferences and workshops.
Expand the number of specialization areas available to PhD students. The Department will consider more
applied PhD tracts in areas like bioinformatics and computational methods for “big data.” The Department
17
-
will also explore the creation of dual degree programs with other programs, e.g., geosciences, astronomy, and
the social sciences.
Revisit the list of courses that graduate students are required to take, and reconsider the emphasis given to
various courses in the curriculum.
In the area of recruiting, the department is reviewing its recruitment procedures and redoubling its effort to
attract top quality doctoral students. Beginning in the fall of 2014, graduate student stipends were increased by
approximately 45% to $20,000 per academic year; this increase makes TAMU graduate student stipends
commensurate with the stipends received by students at our peer institutions. The Department also streamlined its
electronic application procedure and in late February of 2015 sponsored its first Graduate Student Visitation Day.
All admitted applicants to the graduate program who were currently residing in the continental United States were
provided funds to visit the department on February 27, 2015. During the visitation day, several faculty provided
overviews of their research to the students, and the students were familiarized with the Department and campus. A
reception was held that evening at the home Dr. Raymond Carroll. Nine of our top thirteen domestic candidates
attended this event, and we expect to attract at least four of them to TAMU next fall.
Graduate students in the department play a proactive role in departmental life. In 2009 the Statistics Graduate
Student Association was formed. A brief description of SGSA activities is provided on page 54.
18
Professional Education
The Department of Statistics enrolled its first class into the Master of Science in Analytics program in the Fall
of 2013. The program, which is jointly offered with the Mays Business School, offers business and statistics courses
to strengthen the quantitative skills of professionals with strong backgrounds in the sciences, mathematics, and
engineering fields. Students entering this program acquire quantitative skills applicable in a wide variety of business
environments, including manufacturing, utilities, information technologies, healthcare, natural resource management,
transportation, supply chain management, finance and insurance, and energy production.
Through the efforts of the Academic Director for MS Analytics and Online Programs, Dr. Simon Sheather,
the MS Analytics program obtained two large grants from SAS that facilitated the rapid growth of the program during
its first two years. In the Fall of 2014 the program enrolled 28 students, and the Department anticipates that it will
enroll as many as 40 students in the Fall of 2015. This represents remarkable growth in enrollments in a field that has
become highly competitive over the last five or so years.
The Department’s support of professional education is unique among science departments in the College and
reflects the diverse range of employment opportunities that exist for undergraduate and graduate students who have
training in statistical science. Further details regarding the program are provided in Appendix B.
19
Challenges and Opportunities
Figure 1.
Figure 1 illustrates the decline in faculty strength from 2006 to 2014. This decline has adversely affected the
Department’s international reputation and rating, as well as its performance on key indicators in assessing progress
toward Vision 2020 goals. Although three faculty losses since 2008 have been due to retirement, seven other
prominent faculty members left the Department between 2006-2014 for other reasons (Dahl, Genton, Liang (on leave
without pay; resigned spring 2015), Ma, Lahiri, Wang, West). These individuals were high performing, mid-career
faculty members who generated numerous publications, citations and grant funding. It is important to note that
the decline in the size of the Department’s faculty has occurred during a rapid expansion in the size of the
University since 2006, and that the University will continue to grow as the College of Engineering expands
to 25,000 students by the year 2025.
20
The genesis for these losses stem from multiple sources and vary from one faculty member to another, but
common among them were salaries that were not competitive given their research productivity and external funding
records. In at least three of the seven cases noted above, departing faculty received salary increases of greater
than 40% when they left TAMU, and these salary increases were provided by non-peer institutions whose
academic reputations are not comparable to Texas A&M University.
To stem the further loss of our most productive research faculty, the salary “savings” accrued from the loss
of one of the departing faculty members was used to provide equity increases to a number of the Department’s most
productive remaining senior faculty members. These equity adjustments did, however, result in the loss of an
additional faculty line within the Department, and salary inequities continue to be an issue for the Department.
Furthermore, this issue is likely to become more severe as the Department attempts to make replacement hires for
lost faculty. The starting salaries required to attract new assistant professors from leading doctoral programs
now exceeds the salaries currently provided to the outstanding assistant professors that the department
hired only two years ago. Indeed, starting salaries of new assistant professors will soon eclipse the salaries
of our remaining associate professors, and it is likely that the Department failed to hire a highly recruited
assistant professor candidate in Spring 2015 because it was unable to make a competitive salary offer.
Ironically, the success of our faculty (particularly of our junior faculty) is likely to lead to additional attrition
if the Department is unable to provide additional equity adjustments for its most productive members,
particularly among our junior and mid-career faculty.
The problem of retaining faculty is further exacerbated by the relative geographical isolation of Texas A&M
University: Several of our most productive junior faculty have spouses that have been unable to find suitable
employment in College Station and so instead currently work in Houston.
21
Assessment
As noted above, the University has identified a number of key metrics for the evaluation of the Department.
The values of metrics used in this assessment are compiled by Academic Analytics, and our performance on the
metrics is judged against a group of peer institutions identified in Vision 2020. This peer group includes the following
institutions:
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
University of California at Berkeley2/15
University of California at Los Angeles30/30
University of Michigan12/15
University of North Carolina12/20
Georgia Institute of Technology (not included in Academic Analytics summaries of statistics departments)
University of California at San Diego
University of California at Davis27
University of Illinois at Urbana-Champaign34
University of Wisconsin12
University of Florida30
University of Washington3/7
Pennsylvania State University20
University of Texas at Austin
Ohio State University27
University of Maryland
Purdue University24
University of Minnesota20/24
Indiana University
Michigan State University47
Superscripts in this list denote the 2014 US News and World Report rankings of statistics/biostatistics
departments. The Department of Statistics at Texas A&M University ranked 15th (out of 86 programs evaluated).
22
Figure 2 provides a summary of the Department’s performance on a variety of academic metrics (plot
generated by Academic Analytics). This plot is based on a comparison with 18 other statistics departments at research
universities granting doctoral degrees. As this figure demonstrates, the Texas A&M University Department of
Statistics excels in essentially all areas of faculty evaluation within this broad comparison group.
Figure 2.
23
Unfortunately, concerns over propriety of data preclude the display of similar diagnostics within our Vision
2020 peer group. For this reason, data from Academic Analytics reports has been redacted and displayed in Table 1,
which lists the Department’s ranking among our 18 peer institutions on key indicators of productivity. Note that
University of Florida (AG), which contains only one faculty member, has been excluded from the rankings (though
their main statistics department is included) and that Georgia Tech does not have a statistics department. These
rankings are based on publications, citations and grant information collected from 2010-2013.
Table 1.
Metric
Number of faculty with journal publication
Journal publications per faculty member
Percentage of faculty with journal publication
Total journal publications
Citations per faculty member
Number of faculty with citation
Percentage of faculty with citation
Total citations
Grant dollars per faculty member
Grants per faculty member
Total grant dollars
Total number of grants
Awards per faculty member
Number of faculty members with awards
Percentage of faculty with Award
Total awards
Ranking among 18 peer institutions
4
9
14
4
9
3
13
6
8
14
8
7
5
2
4
2
There are two general trends apparent from Table 1. First, the Department, as a whole, typically ranks in the
top half, and for many metrics in the top quarter, of our Vision 2020 peers.
Second, the Department is less successful on several key metrics that involve the percentages of faculty
achieving the outcomes associated with these metrics. This feature of the rankings can be attributed to a small
proportion of our faculty that has not been research active in recent years. The department is currently working to
address this problem and has recently adopted bylaws that impose minimum publication standards for faculty to
maintain in order to avoid unsatisfactory ratings in annual and post-tenure reviews (see Appendix J.).
24
Despite limitations that the Department’s salary structure imposes on retaining and recruiting
quality faculty, as well as the decline in the size of the faculty, the Department is poised to make significant
improvements to its undergraduate and graduate programs . The addition of new faculty lines stemming from
the anticipated success of the undergraduate major in statistics is likely to provide funding for 3-4 additional faculty
lines. Changes to the graduate program will help the Department recruit better graduate students, and will decrease
the average time required for students to complete their graduate studies. The Department extracts great benefit from
its distance learning programs. These programs enhance the reputation of the Department and provide critical
revenue to support graduate students, senior lecturers, on-campus research workshops, and student and faculty travel
to scientific conferences. With only a moderate increase in institutional support, it is likely that the Department could
achieve a top 10 national ranking, among both public and private universities, in most external evaluations of academic
programs.
Key resources required by the department include the following:
i) One 250+ seat classroom dedicated to the Department for service teaching. As indicated above,
the department is not able to teach its service courses in large classroom settings. This restricts
the number of students that can be enrolled in these courses, as well as the number of courses
that the department is able to offer.
ii) An increase in-state graduate course fees from $69/credit hour to $150/credit hour. This will
allow the department to expand its distance learning master’s program to in-state students.
iii) Reimbursement for graduate course fees for students exempted by the Hazelwood Act. The
department has not actively recruited active duty military into the distance learning program
because doing so would result in a significant increase in program costs without offsetting revenue.
iv) Equity increases for the Department’s most highly productive junior and mid-career level
researchers.
v) Reinstatement of teaching fees to replace IEEF funds. The Department’s IEEF and IEEFreplacement funds for FY13, FY14, and FY15 were $485,010, $436,811, and $388,523, respectively
(please refer to Figure 3). This consistent reduction in teaching support has resulted in the loss of a
senior lecturer and has further denigrated the Department’s ability to provide service teaching.
25
Figure 3.
IEEF & IEEF Replacement Funds
IEEF Funds
$485,010
Fiscal Year 2013
$436,811
Fiscal Year 2014
$388,523
Fiscal Year 2015
26
II.
Student Report
27
Graduate Program in Statistics
The Department of Statistics offers a graduate program, leading to the degrees of Master of Science and Doctor
of Philosophy. The Department also jointly sponsors graduate work with all subject matter area departments in setting
up flexible minor programs in statistics.
The Department of Statistics offers two options in its master's degree programs: (1) the Master of Science degree
(thesis option) which requires the preparation of a thesis and (2) the Master of Science (non-thesis option) which
requires more formal course work in lieu of the thesis. Within either option, students are allowed to choose either a
broad-based or specialized program of study. All choices, however, provide a balanced training in statistical methods,
computational statistics, and statistical theory, and are intended to prepare the student to adapt statistical
methodologies to practical problems.
The aim of the Ph.D. program is to provide comprehensive and balanced training in statistical methods,
computational statistics, and the theory of statistics. Particular emphasis is placed on training students to
independently recognize the relevance of statistical methods to the solution of specific problems and to enable them
to develop new methods when they are needed. The training aims to convey a sound knowledge of existing statistical
theory, including the mathematical facility to develop new results in statistical methodology. At the same time, the
program is kept sufficiently flexible to permit students to develop their specific interests.
28
Master of Science Program
Non-Thesis Option
A student seeking the Master of Science degree under the Non-Thesis Option must fulfill the following
requirements:
A. Coursework. Note that STAT 601, 651, 652, and 658 may not be used to fulfill any of the coursework requirements
listed below.
1) STAT 604, 608, 641 and 642.
2) One credit hour of STAT 681.
3) Two semester credit hours of statistical consulting experience (STAT 684) earned in a minimum of two
semesters. Rules governing completing this requirement are given below in Item B.
4) Three semester credit hours of STAT 685 for the preparation of a special problem (see item C below).
5) Eighteen semester credit hours based on one of the emphasis areas outlined below.
6) A total of 36 semester credit hours.
Broad-Based Plan
1) STAT 610, 611
2) Four additional courses from the MS elective courses list.
Biostatistics Emphasis
1) STAT 610, 611, 645 and 646
2) Two additional courses from the MS elective courses list.
Computational Emphasis
1) STAT 610 and 611
2) Two courses in Mathematics (e.g., MATH 609, MATH 610 or MATH 660).
3) Two courses in Computer Science (e.g., CPSC 603, CPSC 654 or CPSC 659).
Applied Emphasis
1) STAT 630, 657
2) Four additional courses from the MS elective courses list.
MS Elective Courses:
STAT 607, 626, 636, 638, 645, 646, 647, 656, 657, 659
B. Substitution of STAT Ph.D. Courses for MS Coursework.
With the approval of the Graduate Advisor and/or Associate Department Head, STAT Ph.D. courses can be
used as substitutes for any of the MS courses listed in part A.
C. Consulting Experience. One semester credit hour of STAT 684 can be obtained through the completion of any
of the experiences listed below.
1) One semester of service in the Statistical Consulting Center.
2) One semester of a departmentally approved internship.
29
3) Special experiences, with prior approval from the Department Head or the Associate Department Head that
involves the following:
a. At least one semester of activity
b. The application of statistical knowledge
c. Working with non-statisticians
d. Sufficient statistical supervision.
D. Form a master's advisory committee and complete a special project under the direction of the chairman of the
advisory committee. Three semester credit hours of STAT 685 are earned by completion of this project. Upon
completion, the student is required to compose a written report and make an oral presentation on the work. The
purpose of this project is to familiarize the student with the type of problems that may be encountered in future
work and to give the student a chance to develop the ability to present results both verbally and in writing. In
many cases, work done during an internship may be used as the basis for the student's master's project. However,
this project must be completed under the supervision of the chairperson of the student's advisory committee.
E. Pass the departmental MS examination (see below).
F. Pass a final oral examination. This examination is concerned with the student's coursework and special problem.
It is administered by the student's advisory committee.
Thesis Option
A student seeking the Master of Science degree under the Thesis Option must fulfill the following requirements:
A. Coursework. Note that STAT 601, 651, 652, and 658 may not be used to fulfill any of the coursework requirements
listed below.
1)
2)
3)
4)
STAT 604, 608, 610, 611, 641 and 642.
One credit hour of STAT 681.
Six semester credit hours of STAT 691 for preparation of a thesis (see item B below).
Nine semester credit hours based on one of the emphasis areas outlined below. STAT 691 semester credit
hours may not be used to satisfy this requirement.
5) A total of 34 semester credit hours.
Broad-Based Plan
1) Three additional courses from the MS elective courses list.
Biostatistics Emphasis
1) STAT 643 and 644
2) One additional courses from the MS elective courses list.
Computational Emphasis
1) At least one course in Mathematics (e.g., MATH 609, MATH 610 or MATH 660).
2) At least one course in Computer Science (e.g., CPSC 603, CPSC 654 or CPSC 659).
B. Substitution of STAT Ph.D. Courses for MS Coursework.
With the approval of the Graduate Advisor and/or Associate Department Head, STAT Ph.D. courses can be
used as substitutes for any of the MS courses listed in part A.
30
C. Form an advisory committee and complete a thesis under the direction of the chairman of the advisory
committee. The Department does not insist that this represent an original contribution to the field of statistics. It
is intended to train the student in carrying out independently a piece of research; this may represent an application
of existing statistical methods in a new area or a comparative evaluation of statistical methods.
D. Pass the departmental MS examination (see below).
E. Pass a final oral examination. This examination is concerned with the student's coursework and thesis. It is
administered by the student's advisory committee.
Master's Diagnostic Examination
The MS examination covers basic statistical methods. The examination is evaluated with the performance judged
to be “Pass” or “Fail.” To receive a Master's Degree, a student must take and pass the exam.
The diagnostic exam is offered twice a year--prior to the beginning of the fall semester and prior to the beginning
of the spring semester, and must be taken at the earliest possible time after the student has completed the required
courses: STAT 610, 611 (or 630), 604, 608, 641, and 642. Any exception to this time limit must be obtained in writing
from the head of the Department.
The results of a student's examination are reported to the faculty of the Statistics Department. If the student's
performance is judged to be deficient, the examination may be retaken the next time it is offered. Only one retake of
the examination is allowed.
The Ph.D. Qualifying Examination can be taken as a substitution for the Master’s Diagnostic Examination. A
student must receive a Pass at the MS level or a Pass at the Ph.D. level on the Ph.D. Qualifying Examination in order
for the results from the Ph.D. Exam to qualify as a Pass on the MS Exam.
31
Doctor of Philosophy Program
The breadth of the field of statistics as well as the frontiers of knowledge in a particular research area are
emphasized in the Ph.D. program. The student seeking a Ph.D. in statistics is required to fulfill the following
requirements. A Ph.D. selection committee will examine the background of entering students to determine if they
have the appropriate mathematics/statistics background to successfully complete the program. Those students
determined to not have the appropriate background will need to complete some courses in the MS STAT program
and/or courses in mathematics.
A. Courses
1) Required Courses – STAT 605, 612, 613, 614, 620, 632, 648
2) At least five courses from the elective course list provided below.
3) Two semester credit hours of statistical consulting experience (STAT 684) earned in a minimum of two
semesters. Rules governing acceptable methods for completing this requirement are given below in Item B.
4) Four semester credit hours of STAT 681.
5) A sufficient number of research hours, STAT 691, or additional courses from the Ph.D. Elective Course list
or M.S. Elective Courses to achieve a total of at least 96 semester credit hours beyond a Bachelor's degree or
64 semester credit hours beyond a Master's degree.
Ph.D. Elective Courses:
STAT - 615, 616, 618, 621, 627, 631, 633, 642, 643, 644, 647, 665, 673, 674, 689
B. Consulting Experience. One semester credit hour of STAT 684 can be obtained through the completion of any
of the experiences listed below.
1) One semester of service in the Statistical Consulting Center.
2) One semester of a departmentally approved Internship.
3) Special experiences, with prior approval from either the Department Head or the Associate Department Head
that involve the following:
a. At least one semester of activity
b. The application of statistical knowledge
c. Working with non-statisticians
d. Sufficient statistical supervision.
C. Ph.D. Qualifying Examination. The Ph.D. Qualifying Exam will cover the material from the required courses:
STAT 614, 620, 612, 613, 605, 648. The student’s performance on the Ph.D. Qualifying Exam combined with the
student’s performance in the required courses will then be evaluated as
1) Pass at the Ph.D. level
2) Pass at the Ph.D. level conditional on retaking specified courses
3) Pass at the M.S. level with no option to retake the Ph.D. exam
4) Fail the exam with no option to retake the Ph.D. exam.
The exams will be offered in May every year approximately two weeks after the spring semester final exams. There
are two schedules for a student to take the Ph.D. qualifying exam.
32
Schedule I: Exam is taken in May of the first academic year student is enrolled in the Ph.D. program.
Schedule II: Exam is taken in May of the second academic year that student is enrolled in the Ph.D. program.
This schedule is for students that are taking background courses in statistics or mathematics prior to taking the
required Ph.D. courses. A student using Schedule II will be evaluated at the end of their second and third
semesters in the Ph.D. program regarding whether they will be allowed to continue in the Ph.D. program. Any
student who has not taken the Ph.D. exam within two years of their entering the program will automatically be
disqualified from the Ph.D. program.
D. Ph.D. Advisory Committee. After passing the Ph.D. qualifying exam, a student must select a faculty member of
the Department of Statistics to be the student’s Ph.D. advisor and to direct the student’s research. The student
and the selected faculty member should work together to form a Ph.D. advisory committee consisting of two
more members from the statistics faculty and a faculty member outside of the department of statistics. A degree
plan must be submitted using the electronic degree plan at the OGAPS website. The degree plan will include all
required courses, five courses from the Elective Courses list, and sufficient hours to meet OGAPS requirements
as listed above.
E. Take and pass the Preliminary Examination administered by the advisory committee within three semesters after
passing the Ph.D. qualifying exam (see below).
F. Write a Ph.D. Dissertation and pass the final Defense of Dissertation Examination (see below). The presentation
of student’s research in their dissertation defense will be open to the public.
Preliminary Examination
After a student has passed the departmental Ph.D. qualifying examination, formed an advisory committee,
submitted a degree plan and has it approved by OGAPS, a student must take the OGAPS required preliminary
examination. The prelim exam consists of the following parts:
1) A written examination developed by the statistics members of the student’s advisory committee. This exam is
usually waived at the discretion of the departmental committee members.
2) A written examination administered by the member of the student’s advisory committee from outside the
Statistics Department. This examination is usually waived.
3) An oral examination administered by the members of the student’s advisory committee. The oral exam
generally consists of the student presenting a proposal for the student’s Ph.D. dissertation research and
discussing any research results completed at the point of the exam.
Scheduling the preliminary examination can only take place after the student has an approved Ph.D. degree plan
on file with OGAPS. The student must successfully pass the preliminary examination within three semesters after
passing the Ph.D. qualifying exam and at least 14 weeks prior to the date of the dissertation defense. The results of
the examination are reported to OGAPS using the Report of the Preliminary Examination, a form found at the OGAPS
website.
33
The Ph.D. Dissertation
After successfully completing all the required courses and passing the Ph.D. Qualifying Exam, a period of time is
to be devoted to formulating a research topic in either statistical methodology or statistical theory under the guidance
of the student's dissertation advisor. The proposed research will be presented to the student’s advisory committee
during the Preliminary Exam in order to obtain the committees input on the appropriateness of the research. The
results of this research must be communicated in a written dissertation satisfying the guidelines established by
OGAPS. The research must constitute an original contribution to the science of statistics and may derive new results
in statistical theory or methodology or may be concerned with developing statistical methodology in new areas of
application.
Once the student's advisory committee feels that the student has completed the dissertation, a final oral
examination is conducted by the advisory committee in which the student defends the dissertation. This exam must
be scheduled by submitting the Request and Announcement of the Final Examination form to OGAPS at least 10
working days before the final exam date.
34
Internship Program
Students after one year of coursework are eligible to participate in an internship with a sponsoring company,
hospital, or federal agency. The internships are generally a semester's stay at the sponsor's site. If a student
participates in one of the internship programs approved by the department head, then the student is given credit for
one hour of STAT 684.
In many cases, work done during the internship may be used as the basis for a Master’s project. However, this
project must be completed under the supervision of the chairperson of the student’s advisory committee.
35
Undergraduate Course Offerings
201. Elementary Statistical Inference. (3-0). Credit 3. Data collection, tabulation, and presentation. Elementary
description of the tools of statistical inference; probability, sampling, and hypothesis testing. Applications of
statistical techniques to practical problems. May not be taken for credit after or concurrently any other course in
statistics or INFO 303 has been taken.
211. Principles of Statistics I. (3-0). Credit 3. Introduction to probability and probability distributions. Sampling
and descriptive measures. Inference and hypothesis testing. Linear regression, analysis of variance. Prerequisite:
MATH 152 or 172.
212. Principles of Statistics II. (3-0). Credit 3. Design of experiments, model building, multiple regression,
nonparametric techniques, contingency tables, and short introductions to response surfaces, decision theory and
time series data. Prerequisite: STAT 211.
301. Introduction to Biometry. (3-0). Credit 3. Intended for students in animal sciences. Introduces fundamental
concepts of biometry including measures of location and variation, probability, tests of significance, regression,
correlation, and analysis of variance which are used in advanced courses and are being widely applied to animaloriented industry. Credit will not be allowed for more than one of STAT 301, 302 or 303. Prerequisite: MATH 141
or 166 or equivalent.
302. Statistical Methods. (3-0). Credit 3. Intended for undergraduate students in the biological sciences and
agriculture (except agricultural economics). Introduction to concepts of random sampling and statistical inference;
estimation and testing hypotheses of means and variances; analysis of variance; regression analysis; contingency
tables. Credit will not be allowed for more than one of STAT 301, 302 or 303. Prerequisite: MATH 141 or 166 or
equivalent.
303. Statistical Methods. (3-0). Credit 3. Intended for undergraduate students in the social sciences. Introduction
to concepts of random sampling and statistical inference, estimation and testing hypotheses of means and variances,
analysis of variance, regression analysis, contingency tables. Credit will not be allowed for more than one of STAT
301, 302 or 303. Prerequisite: MATH 141 or 166 or equivalent.
307. Sample Survey Techniques. (3-0). Credit 3. Concepts of population and sample; the organization of a sample
survey; questionnaire design. Basic survey designs and computation of estimates and variances. Prerequisites: STAT
301, 302, 303, or INFO 303.
407. Principles of Sample Surveys. (3-0). Credit 3. Principles of sample surveys and survey design; techniques for
variance reduction; simple, stratified and multi-stage sampling; ratio and regression estimates; post-stratification;
equal and unequal probability sample. Prerequisite: STAT 212.
408. Introduction to Linear Models. (3-0). Credit 3. Introduction to the formulation of linear models and the
estimation of the parameters of such models, with primary emphasis on least squares. Application to multiple
regression and curve fitting. Prerequisites: MATH 304; STAT 212.
414. Mathematical Statistics. (3-0). Credit 3. Introduction to the mathematical theory of statistics, including
random variables and their distributions, expectation and variance, point estimation, confidence intervals and
hypothesis testing. Prerequisite: MATH 221, 251 or 253.
485. Problems. Credit 1 to 6. Special problems in statistics not covered by another course in the curriculum. Work
may be in either theory or methodology. Prerequisite: Approval of instructor.
36
Graduate Course Offerings
601. Statistical Analysis. (3-2). Credit 4. For students in engineering, physical, and mathematical sciences.
Introduction to probability, probability distributions, and statistical inference; hypotheses testing; introduction to
methods of analysis such as tests of independence, regression, analysis of variance with some consideration of
planned experimentation. Prerequisite: MATH 152 or 172.
604. Topics in Statistical Computations. (3-0). Credit 3. Efficient uses of existing statistical computer programs
(SAS, R, etc.), generation of random numbers; using and creating functions and subroutines; statistical graphics;
programming of simulations studies; and data management issues. Prerequisites: MATH 221, 251, or 253.
605. Advanced Statistical Computations. (3-0). Credit 3. Programming languages, statistical software, and
computing environments; development of programming skills using modern methodologies; data extraction and
code management; interfacing lower-level languages with data analysis software; simulation; MC integration; MCMC procedures; permutation tests; bootstrapping. Prerequisite: STAT 612 and STAT 648.
607. Sampling. (3-0). Credit 3. Planning, execution and analysis of sampling from finite populations; simple,
stratified, multistage and systematic sampling; ratio estimates. Prerequisite: STAT 601 or 652 or concurrent
enrollment in STAT 641.
608. Regression Analysis. (3-0). Credit 3. Multiple, curvilinear, nonlinear, robust, logistic and principal components
regression analysis; regression diagnostics, transformations, analysis of covariance. Prerequisite: STAT 601 or 641.
610. Theory of Statistics - Distribution Theory. (3-0). Credit 3. Brief introduction to probability theory;
distributions and expectations of random variables, transformations of random variables, and order statistics;
generating functions and basic limit concepts. Prerequisite: MATH 409 or concurrent enrollment in MATH 409.
611. Theory of Statistics - Inference. (3-0). Credit 3. Theory of estimation and hypothesis testing; point estimation,
interval estimation, sufficient statistics, decision theory, most powerful tests, likelihood ratio tests, chi-square tests.
Prerequisite: STAT 610 or equivalent.
612. Theory of Linear Models. (3-0). Credit 3. Matrix algebra for statisticians, Gauss-Markov theorem; estimability;
estimation subject to linear restrictions; multivariate normal distribution; distribution of quadratic forms; inferences
for linear models; theory of multiple regression and AOV; random- and mixed-effects models. Prerequisite: Course
in linear algebra.
613. Statistical Methodology I. (3-0). Credit 3. Elements of likelihood inference; exponential family models; group
transformation models; survival data; missing data; estimation and hypothesis testing; nonlinear regression models;
conditional and marginal inferences; complex models-Markov chains, Markov random fields, time series, and point
processes. Prerequisite: STAT 612.
614. Probability for Statistics. (3-0). Credit 3. Probability and measures; expectation and integrals, Kolmogorov's
extension theorem; Fubini's theorem; inequalities; uniform integrability; conditional expectation; laws of large
numbers; central limit theorems. Prerequisite: STAT 610 or its equivalent.
615. Stochastic Processes. (3-0). Credit 3. Survey of the theory of Poisson processes, discrete and continuous time
Markov chains, renewal processes, birth and death processes, diffusion processes, and covariance stationary
processes. Prerequisites: STAT 611; MATH 409.
37
616. Statistical Aspects of Machine Learning I: Classical Multivariate Methods. (3-0). Credit 3. Core methods
from traditional multivariate analysis and various extensions. Probability distributions of random vectors and
matrices, multivariate normal distributions, model assessment and selection in multiple regression, multivariate
regression, dimension reduction, linear discriminant analysis, logistic discriminant analysis, cluster analysis,
multidimensional scaling and distance geometry, and correspondence analysis Prerequisites: STAT 611 and 612.
618. Statistical Aspects of Machine Learning II: Modern Techniques. (3-0). Credit 3. Second course in
statistical machine learning. Recursive partition and tree-based methods, artificial neural networks, support vector
machines, reproducing kernels, committee machines, latent variable methods, component analysis, nonlinear
dimensionality reduction and manifold learning, matrix factorization and matrix completion, statistical analysis of
tensors and multi-indexed data. Prerequisites: STAT 610, 611, and 613.
620. Asymptotic Statistics. (3-0). Credit 3. Review of basic concepts and important convergence theorems;
elements of decision theory; delta method; Bahadur representation theorem; asymptotic distribution of MLE and
the LRT statistics; asymptotic efficiency; limit theory for U-statistics and differential statistical functionals with
illustration from M-,L-,R-estimation; multiple testing. Prerequisite: STAT 614.
621. Advanced Stochastic Processes. (3-0). Credit 3. Conditional expectation; stopping times; discrete Markov
processes; birth-death processes; queuing models; discrete semi-Markov processes; Brownian motion; diffusion
processes, Ito integrals, theorem and limit distributions; differential statistical functions and their limit distributions;
M-,L-,R-estimation. Prerequisite: STAT 614 or STAT 615.
623. Statistical Methods for Chemistry. (3-0). Credit 3. Chemometrics topics of process optimization, precision
and accuracy; curve fitting; chi-squared tests; multivariate calibration; errors in calibration standards; statistics of
instrumentation. Prerequisites: STAT 601 or STAT 652 or STAT 641 or approval of instructor.
626. Methods in Time Series Analysis. (3-0). Credit 3. Introduction to statistical time series analysis;
autocorrelation and spectral characteristics of univariate, autoregressive, moving average models; identification,
estimation and forecasting. Prerequisite: STAT 601 or 642 or approval of instructor.
627. Nonparametric Function Estimation. (3-0). Credit 3. Nonparametric function estimation; kernel, local
polynomials, Fourier series and spline methods; automated smoothing methods including cross-validation; large
sample distributional properties of estimators; recent advances in function estimation. Prerequisites: STAT 611.
630. Overview of Mathematical Statistics. (3-0). Credit 3. Basic probability theory including distributions of
random variables and expectations. Introduction to the theory of statistical inference from the likelihood point of
view including maximum likelihood estimation, confidence intervals, and likelihood ratio tests. Introduction to
Bayesian methods. Prerequisites: Math 221, 251, or 253.
631. Statistical Methods in Finance. (3-0). Credit 3. Regression and the capital asset pricing model, statistics for
portfolio analysis, resampling, time series models, volatility models, option pricing and Monte Carlo methods,
copulas, extreme value theory, value at risk, spline smoothing of term structure. Prerequisites: STAT 610, 611, 608.
632. Statistical Methodology II-Bayesian Modeling and Inference. (3-0). Credit 3. Decision theory;
fundamentals of Bayesian inference; single and multi-parameter models, Gaussian model; linear and generalized
linear models; Bayesian computation; asymptotic methods; non-interative MC; MCMC; hierarchical models;
nonlinear models; random effect models; survival analysis; spatial models. Prerequisite: STAT 613.
38
633. Advanced Bayesian Modeling and Computation. (3-0). Credit 3. Bayesian methodology, and applications
of Bayesian methods in bioinformatics, biostatistics, signal processing, machine learning, and related fields.
Prerequisite: STAT 608, 613, 632.
636. Applied Multivariate Analysis. (3-0). Credit 3. Multivariate extensions of the chi-square and t-tests,
discrimination and classification procedures; applications to diagnostic problems in biological, medical,
anthropological, and social research; multivariate analysis of variance, principal component and factor analysis,
canonical correlations. Prerequisites: MATH 423 and STAT 653 or approval of instructor. Cross-listed with INFO
657.
638. Introduction to Applied Bayesian Methods. (3-0). Credit 3. Students will learn how uncertainty regarding
parameters can be explicitly described as a posterior distribution which blends information from a sampling model
and prior distribution Course will emphasize modeling and computations under the Bayesian paradigm. Topics
include: prior distributions, Bayes Theorem, conjugate and non-conjugate models, posterior simulation via the
Gibbs sampler and MCMC, hierarchical modeling. Prerequisite: STAT 604, 608, or 630.
641. The Methods of Statistics I. (3-0). Credit 3. An application of the various disciplines in statistics to data
analysis, introduction to statistical software; demonstration of interplay between probability models and statistical
inference. Prerequisites: Concurrent Enrollment in STAT 610 or approval of instructor.
642. The Methods of Statistics II (3-0). Credit 3. Design and analysis of experiments; scientific method; graphical
displays; analysis of nonconventional designs and experiments involving categorical data. Prerequisites: STAT 641.
643. Biostatistics I. (3-0). Credit 3. Bio-assay for quantitative and quantal responses; statistical analysis of
contingency, including effect estimates, matched samples and misclassification. Prerequisites: STAT 608, 630, and
642 or STAT 610.
644. Biostatistics II. (3-0). Credit 3. Generalized linear models; survival analysis with emphasis on nonparametric
models and methods. Prerequisites: STAT 643 or approval of instructor.
645. Applied Biostatistics and Data Analysis. (3-0). Credit 3. Survey of crucial topics in biostatistics; application
of regression in biostatistics; analysis of correlated data; logistic and Poisson regression for binary or count data;
survival analysis for censored outcomes; design and analysis of clinical trials; sample size calculation bysimulation;
bootstrap techniques for assessing statistical significance; data analysis using R. Prerequisites: STAT 651, 652, and
659, or equivalent or prior approval of instructor.
646. Statistical Bioinformatics. (3-0). Credit 3. An overview of relevant biological concepts and technologies of
genomic/proteomic applications; methods to handle, visualize, analyze, and interpret genomic/proteomic data;
exploratory data analysis for genomic/ proteomic data; data preprocessing and normalization; hypotheses testing;
classification and prediction techniques for using genomic/ proteomic data to predict disease status. Prerequisites:
STAT 604, 651, 652 or equivalent or prior approval of instructor.
647. Spatial Statistics. (3-0). Credit 3. Spatial correlation and its effects; spatial prediction (kriging); spatial
regression; analysis of point patterns (tests for randomness and modelling patterns); sub sampling methods for
spatial data. Prerequisite: STAT 601 or STAT 611 or equivalent.
648. Applied Statistics and Data Analysis. (3-0). Credit 3. Background to conduct research in the development
of new methodology in applied statistics. Topics covered will include: exploratory data analysis; sampling; testing;
smoothing; classification; time series; and spatial data analysis. Prerequisite: Approval of instructor.
39
651. Statistics in Research I. (3-0). Credit 3. For graduate students in other disciplines; non-calculus exposition of
the concepts, methods and usage of statistical data analysis; T-tests, analysis of variance, and linear regression.
Prerequisite: MATH 102 or equivalent.
652. Statistics in Research II. (3-0). Credit 3. Continuation of STAT 651. Concepts of experimental design,
individual treatment comparisons, randomized blocks and factorial experiments, multiple regression, chi-square
tests and a brief introduction to covariance, non-parametric methods, and sample surveys. Prerequisite: STAT 651.
653. Statistics in Research III. (3-0). Credit 3. Advanced topics in ANOVA; analysis of covariance; and regression
analysis including analysis of messy data; non-linear regression; logistic and weighted regression, diagnostics and
model building; emphasis on concepts, computing and interpretation. Prerequisite: STAT 652.
656. Applied Analytics Using SAS Enterprise Miner. (3-0) Credit 3. Introduction to data mining and will
demonstrate the procedures; Optimal prediction decisions; comparing and deploying predictive models; neural
networks; constructing and adjusting tree models; the construction and evaluation of multi-stage models.
Prerequisite: STAT 657.
657. Advanced Programming Using SAS. (3-0). Credit 3. Programming with SAS/IML, programming in SAS
data step, advanced use of various SAS procedures. Prerequisites: STAT 604, 642.
658. Transportation Statistics. (3-0). Credit 3. Design of experiments, estimation, hypotheses testing, modeling,
and data mining for transportation specialists. Prerequisites: STAT 211 or STAT 651.
659. Applied Categorical Data Analysis. (3-0). Credit 3. Introduction to analysis and interpretation of categorical
data using ANOVA/regression analogs; includes contingency tables, loglinear models, logistic regression; use of
computer software such as SAS, GLIM, SPSSX. Prerequisite: STAT 601 or 641 or 652 or equivalent.
661. Statistical Genetics. (3-0), Credit 3. Basic concepts in human genetics, sampling designs, gene frequency
estimation, Hardy-Weinberg equilibrium, linkage disequilibrium, association and transmission disequilibrium test
studies, linkage and pedigree analysis, segregation analysis, polygenic models, DNA sequence analysis. Prerequisites:
STAT 610 and 611.
662. Advanced Statistical Genetics. (3-0). Credit 3. This course is a continuation of the course, STAT 661
Statistical Genetics. A strong background in statistics, genetics, and mathematics is required. Topics include
counting methods, EM algorithm, Newton's method, scoring in genetics, genetic identity coefficients, descent
graph, molecular phylogeny, models of recombination, sequence analysis, diffusion processes and linkage
disequilibrium mappings. Prerequisite: STAT 610, 611, and 661.
665. Statistical Application of Wavelets. (3-0). Credit 3. This is a course on the use of wavelets methods in
statistics. The course introduces wavelet theory, provides an overview of wavelet-based
statistical methods. Topics include smoothing of noisy signals, estimation function data and representation of
stochastic processes. Some emphasis is given to Bayesian procedures. Prerequisite: STAT 611 or approval by the
instructor.
673. Time Series Analysis I. (3-0). Credit 3. An introduction to diverse modes of analysis now available to solve
for univariate time series; basic problems of parameter estimation, spectral analysis, forecasting and model
identification. Prerequisite: STAT 611 or equivalent.
674. Time Series Analysis II. (3-0). Credit 3. Continuation of STAT 673. Multiple time series, ARMA models, test
of hypotheses, estimation of spectral density matrix, transfer function and forecasting. Prerequisites: STAT 673.
40
681. Seminar. Credit 1. Oral presentations of special topics and current research in statistics. May be repeated for
credit. Prerequisite: Graduate classification in statistics.
684. Professional Internship. Credit 1 to 3. Practicum in statistical consulting for students in Ph.D. program.
Students will be assigned consulting problems brought to the Department of Statistics by researchers in other
disciplines. Prerequisite: STAT 642 or equivalent.
685. Directed Studies. Credit 1 to 6. Individual instruction in selected fields in statistics; investigation of special
topics not within scope of thesis research and not covered by other formal courses. Prerequisites: Graduate
classification and approval of department head.
689. Special Topics in Statistics. Credit 1 to 4. Selected topics in an identified area of statistics. Open to nonmajors. May be repeated for credit. Prerequisite: Approval of instructor.
691. Research. Credit 1 or more. Research for thesis or dissertation. Prerequisite: Graduate classification.
41
Scheduling Coursework
The following list indicates the Department's usual schedule of course offerings. Those courses marked even or
odd are offered only in even numbered and odd numbered years, respectively. Because several courses are offered
only every other year, it is important to plan a program of study and schedule of courses as early as possible.
Course
201
211
212
301
302
303
307
407
408
414
485
601
604
605
607
608
610
611
612
613
614
615
616
618
620
621
623
626
627
630
Semester(s)
Offered
1,2
1,2,3
1,2
1,2
1,2,3
1,2,3
2
1
2
1
1,2,3
1
1,2,3
2
1
2,3
1
2
1
2
1
1 (odd)
1
2
2
2 (even)
4
3
2 (odd)
1,2,3
Course
631
632
633
636
638
641
642
643
644
645
646
647
648
651
652
653
656
657
658
659
661
662
665
673
674
681
684
685
689
691
Semester(s)
Offered
1 (even)
1
2
1
1
1
2
4
4
1
2
1
1
1,2,3
1,2,3
2
2
2
4
2,3
4
4
4
1 (even)
2 (odd)
1,2
1,2,3
1,2,3
4
1,2,3
1: Fall, 2: Spring, 3: Summer, 4: As resources allow.
42
Graduate Program Admissions Criteria
Admissions criteria for the Graduate Program in the Department of Statistics are based on the following
requirements:
o
o
o
o
o
GRE Scores
Transcripts
Resume
3 Letters of Recommendation
Knowledge of Matrix Algebra, along with courses in Calculus I and II, as well as computer
programming
Applicants with a strong background in mathematics, statistics, and computer programming are preferred.
43
GRE Scores for First Time Graduate Students
Major
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
STAT
Semester
Year
Spring 2008
Summer 2008
Fall 2008
Spring 2009
Summer 2009
Fall 2009
Spring 2010
Summer 2010
Fall 2010
Spring 2011
Summer 2011
Fall 2011
Spring 2012
Summer 2012
Fall 2012
Spring 2013
Summer 2013
Fall 2013
Student
Headcount
13
5
59
39
34
83
27
26
81
35
41
109
28
35
93
25
27
62
Average
GRE New
319
318
317
320
317
321
Average
GRE
1249
1176
1251
1291
1270
1246
1354
1288
1300
1276
1368
1334
1193
1337
1364
1400
1262
1297
Minimum
GRE New
299
305
298
312
301
301
Minimum
GRE
1000
1080
780
950
1040
550
1070
1090
1010
970
1180
1060
1120
1190
1170
1390
1100
1100
Maximum
GRE New
334
330
335
327
332
334
Maximum
GRE
1370
1360
1460
1530
1440
1530
1510
1500
1500
1490
1540
1570
1240
1450
1500
1430
1420
1530
44
Graduate Students Applied, Admitted and Enrolled 2007-2009
Applied
Year
2007
Ethnicity
Asian Only
Black Only
Black only + Multiracial w/Black
Hispanic or Latino of
any Race
International
Unknown or Not
Reported
White Only
2007 Total
Asian Only
Black Only
Hispanic or Latino of
any Race
2008
International
Unknown or Not
Reported
White Only
2008 Total
American Indian Only
Asian Only
Black Only
Black only + Multiracial w/Black
2009
Hispanic or Latino of
any Race
International
Unknown or Not
Reported
White Only
2009 Total
Gender
Female
Male
Male
Male
Masters
1
2
1
Male
1
Female
Male
Male
27
22
1
Female
Male
10
14
79
4
8
1
Female
Male
Female
Female
Admitted
Doctoral
1
Doctoral
1
21
36
2
60
1
1
2
18
28
1
Female
Male
14
30
106
2
1
6
6
7
5
2
2
59
Male
Female
1
Male
Female
Male
Female
6
6
14
2
Male
Female
Male
2
31
47
136
26
27
8
6
1
10
14
43
3
6
1
2
1
3
1
Masters
1
8
9
2
20
5
5
1
9
12
35
1
1
11
8
5
1
2
2
2
13
24
47
1
1
1
3
1
1
1
1
5
15
6
6
12
2
5
15
3
27
5
4
4
2
1
17
2
30
47
133
1
1
14
30
61
2
1
6
6
7
5
2
1
Doctoral
1
1
Male
Female
Male
Male
Female
Male
Female
Male
Female
Male
Female
Masters
1
1
1
Enrolled
6
2
2
1
12
6
3
26
1
1
3
4
1
3
14
26
64
1
5
10
3
19
45
Graduate Students Applied, Admitted and Enrolled 2010-2011
Applied
Year
Ethnicity
Asian Only
Black only + Multiracial w/Black
Hispanic or Latino of
any Race
2010
International
Multi-racial excluding
Black
Unknown or Not
Reported
White Only
2010 Total
Asian Only
Black only + Multiracial w/Black
Hispanic or Latino of
any Race
2011
International
Multi-racial excluding
Black
Unknown or Not
Reported
White Only
2011 Total
Gender
Female
Male
Female
Masters
4
7
2
Male
Female
2
3
Male
Female
Male
Female
4
55
51
1
Male
Female
1
16
Male
Female
Male
Female
Male
Female
21
15
45
227
9
11
1
Male
Female
6
3
Male
Female
Male
Female
4
3
6
Male
Female
2
2
Male
Female
Male
23
59
129
Admitted
Doctoral
1
4
Masters
3
7
2
Enrolled
Doctoral
2
2
2
52
70
25
37
5
2
198
3
3
6
1
1
5
4
4
3
6
2
1
13
3
10
23
59
129
1
5
5
11
33
66
7
10
2
2
15
2
2
3
2
1
2
2
1
2
1
2
1
1
2
6
3
3
2
1
Doctoral
2
1
1
1
1
15
42
89
9
11
1
Masters
3
5
2
1
2
6
3
4
1
2
2
1
3
10
17
47
98
3
11
46
Graduate Students Applied, Admitted and Enrolled 2012-2013
Applied
Year
Ethnicity
Asian Only
Black only + Multiracial w/Black
Hispanic or Latino of
any Race
2012
International
Multi-racial excluding
Black
Unknown or Not
Reported
White Only
2012 Total
2013
Asian Only
Black only + Multiracial w/Black
Hispanic or Latino of
any Race
International
Multi-racial excluding
Black
Unknown or Not
Reported
White Only
2013 Total
Admitted
Gender
Female
Male
Female
Masters
5
7
2
Male
Female
3
4
3
4
3
3
Male
Female
Male
Female
5
2
1
1
5
2
1
1
2
1
Male
Female
1
1
1
1
1
1
Male
Female
Male
Female
Male
Female
4
18
48
102
9
7
4
4
18
48
102
9
7
4
2
15
38
76
6
3
3
Male
4
Female
Male
Female
1
Female
2
2
2
Male
Female
Male
2
15
37
82
2
15
37
82
2
11
27
60
1
Doctoral
6
5
4
5
20
1
Masters
5
7
2
Enrolled
Doctoral
6
5
4
5
20
1
4
1
8
2
7
19
1
1
Masters
4
5
1
Doctoral
6
5
2
4
17
4
1
8
2
7
19
1
1
1
8
2
4
15
47
Students by GPR Range
(Cumulative GPR as of the beginning of semester)
Semester
Year
Fall 2008
Real
Major
Classification
Level
STAT
Doctoral
Masters
Fall 2009
STAT
Doctoral
Masters
Fall 2010
STAT
Doctoral
Masters
GPR Range
(Beginning
of Semester)
3.75-4.00
3.50-3.74
3.00-3.49
0 or unknown
3.75-4.00
3.50-3.74
3.00-3.49
2.50-2.99
2.00-2.49
0.01-1.99
0 or unknown
3.75-4.00
3.50-3.74
3.00-3.49
2.50-2.99
3.75-4.00
3.50-3.74
3.00-3.49
2.50-2.99
0 or unknown
3.75-4.00
3.50-3.74
3.00-3.49
0 or unknown
3.75-4.00
3.50-3.74
3.00-3.49
2.50-2.99
2.00-2.49
0.01-1.99
0 or unknown
Student
Headcount
% of
Total
Cumulative
Headcount
Cumulative
%
28
5
12
4
14
12
14
3
3
1
38
34
10
10
1
34
9
19
4
49
31
10
12
1
25
16
20
9
2
1
43
2.82%
0.50%
1.21%
0.40%
1.41%
1.21%
1.41%
0.30%
0.30%
0.10%
3.83%
3.42%
1.01%
1.01%
0.10%
3.42%
0.91%
1.91%
0.40%
4.93%
3.12%
1.01%
1.21%
0.10%
2.52%
1.61%
2.01%
0.91%
0.20%
0.10%
4.33%
28
33
45
49
63
75
89
92
95
96
134
168
178
188
189
223
232
251
255
304
335
345
357
358
383
399
419
428
430
431
474
3%
3%
5%
5%
6%
8%
9%
9%
10%
10%
13%
17%
18%
19%
19%
22%
23%
25%
26%
31%
34%
35%
36%
36%
39%
40%
42%
43%
43%
43%
48%
48
Semester
Year
Real
Major
Classification
Level
Fall 2011
STAT
Doctoral
Masters
Fall 2012
STAT
Doctoral
Masters
Fall 2013
ANLY
Masters
STAT
Doctoral
Masters
Summary
GPR Range
(Beginning
of Semester)
3.75-4.00
3.50-3.74
3.00-3.49
2.50-2.99
0 or unknown
3.75-4.00
3.50-3.74
3.00-3.49
2.50-2.99
2.00-2.49
0.01-1.99
0 or unknown
Student
Headcount
% of
Total
Cumulative
Headcount
Cumulative
%
25
9
11
1
1
25
22
26
9
3
1
51
2.52%
0.91%
1.11%
0.10%
0.10%
2.52%
2.22%
2.62%
0.91%
0.30%
0.10%
5.14%
499
508
519
520
521
546
568
594
603
606
607
658
50%
51%
52%
52%
52%
55%
57%
60%
61%
61%
61%
66%
3.75-4.00
3.50-3.74
3.00-3.49
0 or unknown
3.75-4.00
3.50-3.74
3.00-3.49
2.50-2.99
2.00-2.49
0.01-1.99
0 or unknown
3.00-3.49
0 or unknown
3.75-4.00
3.50-3.74
3.00-3.49
0 or unknown
3.75-4.00
3.50-3.74
3.00-3.49
2.50-2.99
2.00-2.49
0 or unknown
24
7
6
2
24
14
37
8
3
1
36
1
10
24
7
7
4
29
18
28
6
5
34
993
2.42%
0.70%
0.60%
0.20%
2.42%
1.41%
3.73%
0.81%
0.30%
0.10%
3.63%
0.10%
1.01%
2.42%
0.70%
0.70%
0.40%
2.92%
1.81%
2.82%
0.60%
0.50%
3.42%
100.00%
682
689
695
697
721
735
772
780
783
784
820
821
831
855
862
869
873
902
920
948
954
959
993
-
69%
69%
70%
70%
73%
74%
78%
79%
79%
79%
83%
83%
84%
86%
87%
88%
88%
91%
93%
95%
96%
97%
100%
-
49
Institutional Support for Full Time Students
Fiscal Year 2009
Institutional Salary Support
Tuition - Fall, Spring and Summer
College of Science Funded Scholarships
Departmental Funded Scholarships
TOTAL
Fiscal Year 2010
Institutional Salary Support
Tuition - Fall, Spring and Summer
College of Science Funded Scholarships
Departmental Funded Scholarships
TOTAL
Fiscal Year 2011
Institutional Salary Support
Tuition - Fall, Spring and Summer
College of Science Funded Scholarships
Departmental Funded Scholarships
TOTAL
$1,000,125
$278,291
$12,500
$6,800
$1,297,716
Fiscal Year 2012
Institutional Salary Support
Tuition - Fall, Spring and Summer
College of Science Funded Scholarships
Departmental Funded Scholarships
TOTAL
$908,250
$315,387
$83,500
$7,400
$1,314,537
$1,235,225
$341,220
$12,500
$8,600
$1,597,545
Fiscal Year 2013
Institutional Salary Support
Tuition - Fall, Spring and Summer
College of Science Funded Scholarships
Departmental Funded Scholarships
TOTAL
$893,160
$231,101
$69,000
$15,625
$1,208,886
$1,206,680
$315,387
$74,000
$16,000
$1,612,067
Fiscal Year 2014
Institutional Salary Support
Tuition - Fall, Spring and Summer
College of Science Funded Scholarships
Departmental Funded Scholarships
TOTAL
$966,690
$246,739
$27,000
$9,800
$1,250,229
50
Honors & Awards Received by Students
YEAR
STUDENT
Garcia, Tanya
Ghosh, Souparno
2009
Lennox, Kristen
Rolfes, Jennifer
2010
•
Bandyopadhyay, Soutir
Chen, Dai
De, Debkumar
Garcia, Tanya
Kolodziej, Elizabeth
Young
Roh, Soojin
Sin, Ying
Sun, Ranye
Sun, Tanya
Xu, Kun
Xun, Xiaolei
You, Jia
•
•
•
•
•
•
•
•
•
•
•
•
Emanuel Parzen Graduate Research Fellowship
Norbert Hartmann, Jr. Fellowship
Statistics Former Student Fellowship
Philanthropic Educational Organization (PEO) Scholar Award
Distinguished Graduate Student Award for Excellence in Teaching
(University-Wide)
James Goodlett Fellowship
ASA Travel Award SRCOS
Eva & Lee Smith Fellowship
William S. Connor Award
Norbert Hartmann, Jr. Fellowship
Margaret Sheather Memorial Award in Statistics
Ruth & Howard Newton Fellowship
Ball, Robyn
•
•
•
•
•
•
•
•
•
•
•
•
•
•
NASA GSRP Fellowship
Statistics Former Student Fellowship
Eva & Lee Smith Fellowship
Gertrude Cox Scholarship
Statistics Former Student Fellowship
James Goodlett Fellowship
Margaret Sheather Memorial Award in Statistics
JSM Student Paper Award
William S. Connor Award
Emanuel Parzen Graduate Research Fellowship
Statistics Former Student Fellowship
Ruth & Howard Newton Fellowship
Statistics Former Student Fellowship
Norbert Hartmann, Jr. Fellowship
•
•
•
•
•
•
•
•
•
•
Dean’s Graduate Scholarship
Non-Teaching Assistantship
Eva & Lee Smith Fellowship
Philanthropic Educational Organization (PEO) Scholar Award
Eva & Lee Smith Fellowship
Anant M. Kshirsagar Endowed Fellowship in Statistics (Inaugural)
Capital One Modeling Competition
Anant M. Kshirsagar Endowed Fellowship in Statistics (Inaugural)
Eva & Lee Smith Fellowship
Ruth & Howard Newton Fellowship
Garcia, Tanya
Jeong, Jaehong
Pflueger, Michelle
Sarkar, Abhra
Song, Qifan
Xu, Ganggang
Zhang, Bohai
Zhang, Nan
Algeri, Sara
2012
•
•
•
•
Texas A&M University Louis Stokes Alliance for Minority Participation
(TAMUSLSAMP) Fellowship
Emanuel Parzen Research Graduate Fellowship Award
Laha Travel Award
Emanuel Parzen Graduate Research Fellowship Award
Texas A&M University Louis Stokes Alliance for Minority Participation
(TAMUSLSAMP) Fellowship
William S. Connor Award
Xun, Xiaolei
Chen, Shuia
2011
•
AWARD/FELLOWSHIP
Ball, Robyn
Cai, Quan
Cheng, Yichen
Durgin, Bryce
Gregory, Karl
Liang, Liang
51
Little, Alex
Mintz, Steven
Mukhopadhyay,
Subhadeep
Seem, Emily
Shin, Minsuk
Shin, Yei-Eun
Sinha, Shyamalendu
Song, Qifan
Sun, Ranye
Wang, Xiao
Whang, Stephanie
Xu, Ganggang
Xu, Kun
Xue, Jingnan
Xue, Kun
Algeri, Sara
Ball, Robyn
Cai, Quan
Jennings, Elizabeth
Li, Furong
Liang, Liang
Mintz, Steven
Sarkar, Abhra
2013
Seem, Emily
Shin, Yei Eun
Shin, Minsuk
Sinha, Shyamalendu
Song, Qifan
Su, Ya
Wang, Xiao
Xu, Ganggang
Xue, Jingnan
Cai, Quan
Ghosh, Riddhi
He, Kejun
2014
He, Shiyuan
Herta, Patrick
Jennings, Elizabeth
Jreij, Vennessa
Lee, Donghyuk
Liang, Liang
•
•
Margaret Sheather Memorial Award
Ruth & Howard Newton Fellowship
•
Emanuel Parzen Graduate Research Fellowship Award
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Ruth & Howard Newton Fellowship
Statistics Former Student Fellowship
Statistics Former Student Fellowship
Norbert Hartmann, Jr. Fellowship
Norbert Hartmann, Jr. Fellowship
Anant M. Kshirsagar Endowed Fellowship in Statistics (Inaugural)
Capital One Modeling Competition
Norbert Hartmann, Jr. Fellowship
James Goodlett Fellowship
Capital One Modeling Competition
ENAR Distinguished Student Paper Award
William S. Connor Award
James Goodlett Fellowship
Capital One Modeling Competition
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Eva & Lee Smith Fellowship
Philanthropic Educational Organization (PEO) Scholar Award
Eva & Lee Smith Fellowship
Margaret Sheather Memorial Award in Statistics
James Goodlett Fellowship
Norbert Hartmann, Jr. Fellowship
Eva & Lee Smith Fellowship
Ruth & Howard Newton Fellowship
Ruth & Howard Newton Fellowship
JSM SBSS Student Paper Competition Winner
Anant M. Kshirsagar Endowed Fellowship
Statistics Former Student Fellowship
Ruth & Howard Newton Fellowship
Norbert Hartmann, Jr. Fellowship
Statistics Former Student Fellowship
Norbert Hartmann, Jr. Fellowship
Emanuel Parzen Graduate Research Fellowship
William S. Connor Award
James Goodlett Fellowship
Norbert Hartmann, Jr. Fellowship
International Biometric Society’s Easter North American Region
James Goodlett Fellowship
•
•
•
•
•
•
•
•
•
•
Capital One Modeling Competition, 1st Place
OGAPS Dean’s Doctoral Fellowship
Emanuel Parzen Graduate Research Fellowship
Anant M. Kshirsagar Endowed Fellowship
Anant M. Kshirsagar Endowed Fellowship
College of Science Dean’s Doctoral Fellowship
Philanthropic Educational Organization (PEO) Scholar Award
OGAPS Graduate Diversity Fellowship
Anant M. Kshirsagar Endowed Fellowship
Capital One Modeling Competition, 1st Place
52
Liu, Senmao
Metheney, Erica
Niu, Yabo
Peiskee, J.D.
Philbin, Robert
Pugh, Chelsea
Ramalingaiah, Indu
Stabile, Lauren
Sundararajan, Raanju
Wang, Tianying
Wang, Xiao
Wen, Yujin
Xue, Jingnan
Zhang, Bohai
Zhou, Weiyin
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Capital One Modeling Competition, 1st Place
College of Science Dean’s Doctoral Fellowship
College of Science Lechner Fellowship
OGAPS Dean’s Doctoral Fellowship
Capital One Modeling Competition, 3rd Place
College of Science Lechner Fellowship
College of Science Lechner Fellowship
Eva & Lee Smith Fellowship
Norbert Hartmann, Jr. Fellowship
Capital One Modeling Competition, 3rd Place
Ruth & Howard Newton Fellowship
Norbert Hartmann, Jr. Fellowship
Statistics Former Student Fellowship
James Goodlett Fellowship
Anant M. Kshirsagar Endowed Fellowship
OGAPS Dean’s Doctoral Fellowship
College of Science Dean’s Doctoral Fellowship
Capital One Modeling Competition, 3rd Place
Capital One Modeling Competition, 1st Place
William S. Connor Award
Capital One Modeling Competition, 1st Place
Capital One Modeling Competition, 3rd Place
Margaret Sheather Memorial Award in Statistics
53
The Statistics Graduate Student Association
The Statistics Graduate Student Association represents all graduate students in the Department of Statistics
at Texas A&M University. It is led by the elected officers, Mary Frances Dorn (President), Alex Asher (Vice President
and President-elect), Amir Nikooienejad (Treasurer), Shelby Cummings (Secretary), and Quan Cai (Web
Designer). Our mission is to provide the best possible environment to encourage the interaction between students
and faculty by providing forums for students to connect with faculty as they discuss their current research,
encouraging participation in academic events outside of the traditional classroom setting, and by giving back to the
community that supports all of us in the A&M family.
The SGSA organizes a number of academic and professional events throughout the year. One of the most
important functions of the SGSA is to foster connections between the students and faculty. We do this mainly through
informal talks given by faculty about their research interests. On a biennial basis, we also invite a renowned statistician
from outside of our department to give a talk and to meet with our students. We are currently preparing for an annual
workshop on high-performance computing led by our department’s Director of Information Technology.
Additionally, we organize visits by recruiters from a variety of industries. This year, we have already hosted five
recruitment presentations from companies including Shell, Rackspace, and Capital One, and are preparing for another
event next month. Finally, we provide the opportunity for students to give talks in front of their fellow students. This
year, we have scheduled a couple of graduating students to give their practice defense.
The SGSA also serves to bring the students together as a community outside of the workplace. Some of the
social activities this year include an Ultimate Pi Day celebration, a combination game night and Lunar New Year
celebration, pumpkin carving, and bowling. We still have two important events scheduled this semester. One is our
popular Faculty Appreciation Barbecue that brings together students, post docs, faculty, and their families. Another
is our participation as an organization in the Big Event, the campus-wide service project to say “thank you” to the
Bryan/College Station community.
These events, both academic and social, help to bring together the students, whether they are first-years or
finishing their dissertations, both domestic and international. Our continuing goal for the SGSA is to promote and to
strengthen these connections so that all students feel that they are part of the Department of Statistics family.
54
STUDENT PUBLICATIONS 2009-2013
Student Publications
2009
2010
2011
2012
2013
0
2
4
6
8
10
12
14
55
Professional Development Opportunities for Students
The Department of Statistics and Texas A&M University offer a wide range of Professional Development
opportunities to graduate students seeking careers both in and outside of academia. The Statistics Department
provides faculty career advising and mentoring. Students within the department can obtain financial assistance for
opportunities to travel and present at conferences. The Statistics Graduate Student Association (SGSA) hosts several
industry recruitment events each semester to explore professional internships and job opportunities outside of
TAMU. SGSA also holds student panels for those in the program to ask questions about research, advisors, job
hunting and how to succeed in the program. In addition, SGSA hosts workshops, presentations and lunch seminars
with current faculty.
There are currently 8 campus units outside of the Department of Statistics that provide professional
development opportunities for our students: the Career Center, Center for Teaching Excellence, Graduate Student
Council, International Student Services, Office of Graduate and Professional Studies, Student Counseling Center,
University Libraries, and the University Writing Center.
TAMU’s Center for Teaching Excellence (CTE) provides opportunities for current students to enhance their
knowledge and experience as a Teaching Assistant with TA certification, TA mentor training, STEM teaching
professional development courses, teaching seminar series, consulting and more. The CTE also houses the Academy
for Future Faculty which supports graduate students and post-docs in preparation for a career in higher education.
Students can earn an Academy for Future Faculty certificate and can access tools for portfolios and syllabus builders,
attend free seminars and workshops on a range of subjects for teaching in higher education.
The Career Center provides a wide range of services including resume help, career advising, workshops,
internships, mock interviews and career fairs. The Office of Graduate and Professional Studies promotes professional
development in four areas: academic development, leadership and communication, instructions and assessment, and
career development. They provide a search engine for students to identify professional development opportunities
across campus. They have also implemented a 3 Minute Thesis Competition (developed at the University of
Queensland) in which students have three minutes to present a compelling oration on their thesis. The Office of
Graduate and Professional Studies, along with the University Writing Center, also offers thesis/dissertation
workshops and seminars. Along with other resources, the Office of Graduate and Professional Studies and the Career
Center also offer access to the Versatile PhD. This resource is the largest online community for non-academic and
non-faculty careers. MS and PhD students can see real resumes and CV’s, read real success stories and career panels,
consult forums and search for job listings outside academia.
56
AVERAGE YEAR TO DEGREE, BY
DEGREE PROGRAM (STATISTICS)
PhD
MS
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
2006-07
2007-08
Year
2006-07
2007-08
2008-09
2009-10
2010-11
2011-12
2012-13
2008-09
2009-10
Doctoral (PhD)
4.07
3.25
3.90
5.64
5.44
5.46
6.06
2010-11
2011-12
2012-13
Masters (MS)
2.31
2.33
2.77
3.21
2.73
3.01
3.11
57
STAT Masters Graduation and Retention Report
2 - Year
Cohort Year
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Headcount
17
20
9
9
10
14
14
33
36
30
32
46
% Master
Completion
35.30%
35.00%
55.60%
55.60%
70.00%
64.30%
28.60%
24.20%
11.10%
16.70%
9.40%
6.50%
% Retain in
Master
41.20%
50.00%
44.40%
33.30%
10.00%
35.70%
42.90%
33.30%
38.90%
30.00%
28.10%
26.10%
3 - Year
% Master
Completion
82.40%
70.00%
77.80%
100.00%
90.00%
100.00%
64.30%
42.40%
33.30%
36.70%
21.90%
% Retain in
Master
5.00%
11.10%
18.20%
13.90%
3.30%
9.40%
58
STAT Doctoral Graduation and Retention Report
4 - Year
5 - Year
6 - Year
Cohort
_Year
Headcount
% Doctoral
Completion
% Retain in
Doctoral
% Not Enr but
Earn Mas Deg
% Doctoral
Completion
% Retain in
Doctoral
% Not Enr but
Earn Mas Deg
% Doctoral
Completion
% Retain in
Doctoral
% Not Enr but
Earn Mas Deg
2001
14
14.30%
42.90%
14.30%
42.90%
14.30%
14.30%
50.00%
7.10%
14.30%
2002
7
28.60%
28.60%
42.90%
71.40%
28.60%
71.40%
2003
12
41.70%
33.30%
16.70%
83.30%
8.30%
2004
9
44.40%
11.10%
33.30%
66.70%
11.10%
11.10%
77.80%
11.10%
2005
8
37.50%
25.00%
25.00%
50.00%
12.50%
25.00%
62.50%
25.00%
2006
15
13.30%
26.70%
46.70%
46.70%
13.30%
26.70%
60.00%
26.70%
2007
28
17.90%
32.10%
39.30%
53.60%
10.70%
25.00%
67.90%
3.60%
2008
17
29.40%
23.50%
5.90%
47.10%
17.60%
52.90%
5.90%
2009
17
41.20%
35.30%
64.70%
11.80%
2010
22
18.20%
40.90%
28.60%
91.70%
17.90%
27.30%
59
2010
2009
Master’s Degrees Awarded 2009-2014
Name
Ali, Mir Usman
Bergstresser, Dana Lea
Fellman, Bryan Michael
Jann, Dominic Andrew
Krassavine, Konstantin
Li, Jing
Lee, Jun Bum
Longsine, Lindsay Anne
Pan, Ying-An
Perritt, Jon Ross
Pirlepesov, Fakhiriddin
Shoulders, Jeromie Lamun
Walters, Lori Katherine
Wan, Qiujie
Wang, Yiyi
Wei, Shan
Wiley, Allison LuAnn
Xun, Xiaolei
Yang, Zhixian
Ackerman, Clarissa M.
Bankston, Thomas Clifton
Black, Rebecca A.
Bussell, Sammy J. Jr.
Byers, Michael David
Cefalu, Matthew Steven
Chen, Dai
Christensen, Brent Thomas
Decker, Thomas Virgil
Gil, Randall Edward
Hopp, Ashley Jean
Hughes, Kelley Leigh
Kim, Hei Joung
Lane, David Edward
Lu, Ming
Riester, Katherine Demetra
Rolfes, Jennifer A.
Yoo, Seung Yoon
Zhang, Yiwei
Month Received
December
May
December
May
December (Online)
December
May
May
May
August
December
August (Online)
May
August
December
December
May
December
May
December (Online)
December (Online)
August
December (Online)
May (Online)
May
May
May (Online)
May (Online)
May
December (Online)
December (Online)
May
December (Online)
May
December (Online)
August
December
May
Advisor(s)
Boggess/ Longnecker
Sheather/Speed
Boggess/Longnecker
Speed/ Longnecker
Speed/Longnecker
West, W.
Subba Rao, S.
Wehrly, T.
Longnecker/Speed
Longnecker/Boggess
Carroll, R.
Speed/Longnecker
Boggess/Speed
Speed, F.M.
Dahl, D.
Hart, J.
Dabney, A.
Mallick/Carroll
Liang, F.
Sheather, S.
Speed, F.M.
Speed/Longnecker
Speed/ Longnecker
Speed/Longnecker
Longnecker/Boggess
Huang, J.
Speed/Longnecker
Speed/Longnecker
Carroll, R.
Speed/Longnecker
Wehrly/Longnecker
Subba Rao, S.
Speed/Longnecker
Wang, S.
Perrett/Speed
Speed/Longnecker
Sinha, S.
Fan, R.
60
2011
2012
Alzubaydi, Michael J.
Andersen, Clark R.
Cepulch, Gregory Joseph
Chang, Qing
Chown, Justin A.
Dorji, Cheku
Finch, William
Goldsby, Jennifer S.
Greenfield, Jason O’Neal
Gregory, Karl Bruce
Gu, Manxi
He, Zhuoya
Hetz, Shira
Kennedy, Kelly Marie
King, Simon J.
Krutsick, Robert S.
Levine, Ian R.
Little, Bryce P.
Lu, Jianxu
Lydon, Daniel T.
Massey, Ronnie
Oh, Minkyung
Pflueger, Michelle L.
Phillips, Christopher T.
Sheng, Jinfei
Tang, Xincheng
Wang, Jieyu
Zhang, Li Yun
Austria, Gener M.
Barman, Poulami
Bateman, Katherine A.
Bennett, John C.
Blaskowski, Stacie M.
Chen, Shuai
Connelly, Karen E.
Franklin, Cynthia A.
Goddard, Scott D.
Goll, Johannees
Gordon, Charles M.
Gudupuri, Vennela
Hanley-Burkhart, Jennifer E.
Housley, Emily E.
Jennings, Elizabeth M.
Little, Alexander A.
Lucas, William F.
December (Online)
December (Online)
May
December
August
August
May (Online)
December
May (Online)
May
May
December (Online)
May
May
December (Online)
August (Online)
August (Online)
December (Online)
December
December (Online)
May (Online)
May
May (Online)
December
December
December
May
August (Online)
May (Online)
May
August
December (Online)
December (Online)
May
May (Online)
May (Online)
August
August (Online)
May (Online)
August (Online)
May (Online)
August (Online)
August
May (Online)
December
Dabney, A.
Speed/Wehrly
Hart, J.
Fan, R.
Sherman/Jun
Dahm, P.F.
Speed, F.M.
Longnecker, M.
Perrett, J.
Lahiri, S.
Fan, R.
Huang, J.
Sheather, S.
Wehrly, T.
Perrett, J.
Dabney/Longnecker
Dabney/Speed
Dahl, D.
Fan/Longnecker
Dabney, A.
Speed/Longnecker
Sinha, S.
Huang, J.
Dabney, A.
Huang, J.
Dabney, A.
Liang, F.
Dabney, A.
Speed, F.M.
Spiegelman, C.
Longnecker/Speed
Sheather, S.
Sinha, S.
Huang, J.
Wehrly, T.
Wehrly, T.
Genton, M.
Dabney, A.
Sinha, S.
Perrett/Speed
Sinha, S.
Mallick, B.
Carroll, R.
Wehrly, T.
Speed, F.M.
61
2013
McManus, Weston K.
Moody, Grant A.
Napier, Todd A.
Neumann, Anthony M.
Olmstead, Kaitlin S.
Reed, Paul W.
Ryan, Christopher W.
Shetty, Nathan S.
Tuteja, Navneet
Torno, Nathan B.
Tripathi, Anjani
Uppalapati, Deepthi
Wang, Kai-Sin
Wang, Ling
Whitten, Jennifer L.
Williams, Kaylee D.
Yingling, Michael D.
Zhang, Mi
Zhang, Rong
Akdede, Merve
Beck, Sarah J.
Bein, Justin Matthew
Brady, Ryan Douglass
Brown, Angela N.
Cope, Tara Marie
Cox, Cody Lee
Daligou, Servais D.
Dean, Amber E.
Frederiksen, Eric L.
Green, Abigail Brice
Harper, Nathan Lee
Hasbun, Jorge A.
Hong, Ji
Jackson, Steven M.
Jagannathan, Shilpa
Jorgensen, Janine M.
Kim, Jinsu
Kim, Shiheun
Lee, Younguk
Lizarraga, Laci Elizabeth
Martin, Zachary James
Negash, Yonatan
Nimchuk, Nicholas
Phan, Jennifer Lee
Pitts, Mark Anthony
May (Online)
August (Online)
December
May
December (Online)
December (Online)
May (Online)
December (Online)
August (Online)
May
May (Online)
December (Online)
December
December (Online)
December (Online)
May (Online)
December (Online)
May (Online)
May (Online)
August
December (Online)
December (Online)
August (Online)
May (Online)
August (Online)
August (Online)
August (Online)
May (Online)
May (Online)
December (Online)
December (Online)
May (Online)
August (Online)
May (Online)
December
May (Online)
December
December
August
December (Online)
August (Online)
December (Online)
May (Online)
December (Online)
December (Online)
Speed, F.M.
Toby, E.
Longnecker, M.
Longnecker, M.
Cline, D.
Jun, M.
Dabney, A.
Spiegelman/Mallick
Huang/Longnecker
West, W.
Mallick, B.
Dahl, D.
Longnecker, M.
Speed, F.M.
Wehrly, T.
Mallick, B.
Wehrly, T.
Huang, J.
Hart, J.
Longnecker, M.
Dabney, A.
Spiegelman, C.
Spiegelman, C.
Wehrly, T.
Wehrly, T.
Huang, J.
Mallick, B.
Hart, J.
Huang, J.
Sinha, S.
Dabney, A.
Dabney, A.
Pourahmadi, M.
Cline, D.
Longnecker, M.
Carroll, R.
Huang, J.
Longnecker, M.
Jones, E.
Dabney, A.
Jones, E.
Jones, E.
Spiegelman, C
Huang, J.
Speed, F.M.
62
2014
Platt, Stephanie Ross
Poole, Jason Eugene
Roychowdhury, Lakshmi
Stolz, Phillip Lawrence
Walker, Tobias
Whang, Stephanie S.
Wilson, Celeste K.
Wong, Yuen Sum
Algeri, Sara
Aucoin, Deron Lane
Beltramo, Alvin F.
Bessinger, Alexander M.
Byler, Daniel Mahlon
Chapman, Richard Scott
Costello, Lance John
Davis, Taylor K.
Evert, Daniel James
Fetzer, Jeffrey R.
Galang, Joel Samson
Goldsmith, Anne Wiley
Goodhue, Jonathan Thiel
Gosink, John Joseph
Govan, Barney
Hejmadi, Uday
Hosek, Kathleen
Johnson, Kurt Benjamin
Joseph, James A.
Kreisler, Craig Jordan
Lee, Melissa Michelle
Li, Kelvin
Liu, Dan
Lucas, Geoffrey M.
Magagnoli, Joseph Carlo
Morse, Jennifer Lee
Olivares, Rolando Javier
Pestrivok, Aleksei
Philbin, Robert A.
Przybylinski, Eric Brady
Roane, Warren Maurice
Rodriguez, Christopher Jessie
Scott, Zachary M.H
Szydziak, Elisa
Temple, Samuel Robert
Tran, Hung Manh
Vu, Cong-Tam Dinh
August (Online)
December (Online)
May
December (Online)
May (Online)
May
May (Online)
December (Online)
August
December (Online)
August (Online)
May (Online)
December (Online)
August (Online)
August (Online)
May (Online)
December (Online)
May (Online)
May (Online)
August
December (Online)
December (Online)
May (Online)
August (Online)
May (Online)
December (Online)
May (Online)
May (Online)
May (Online)
December (Online)
August (Online)
December (Online)
December (Online)
May (Online)
May
August (Online)
August (Online)
December (Online)
August (Online)
May (Online)
May (Online)
May (Online)
May (Online)
May (Online)
May (Online)
Sheather, S.
Dabney, A.
Lahiri, S.
Dahm, P. F.
Dabney, A.
Huang, J.
Sherman, M.
Huang, J.
Johnson, V.
Zhou, L.
Dabney, A.
Sheather, S.
Sheather/Katzfuss
Sheather, S.
Sheather, S.
Sheather, S.
Sheather, S.
Dabney, A.
Sheather, S.
Hart, J.
Sheather/Katzfuss
Zhou, L.
Huang, J.
Sheather, S.
Sheather, S.
Jones, E.
Sheather, S.
Sinha, S.
Spiegelman, C.
Sheather/Katzfuss
Sheather, S.
Zhou, L.
Sheather, S.
Sheather, S.
Longnecker, M.
Sheather, S.
Jun, M.
Zhou, L.
Sheather/Katzfuss
Sheather, S.
Wehrly, T.
Sheather, S.
Sheather, S.
Sheather, S.
Longnecker, M.
63
Walsh, Colm
Wang, Ruoxin
Wilkerson, Huiwen
Womack, Scott Forrest
Zhang, Wenling
Zhou, Qian
Zhou, Weiyin
May (Online)
August
May (Online)
May (Online)
August(Online)
May
May(Online)
Jones, E.
Wang, S.
Dabney, A.
Jun, M.
Jones, E.
Longnecker, M.
Dabney, A.
64
2009
Ph.D. Degrees Awarded 2009-2014
Name
Dissertation Title
Advisor(s)
Ghosh, Souparno
Herring, Amanda
Scott
Copula Based Hierarchical Bayesian Models (August)
Space-Time Forecasting and Evaluation of Wind Speed
with Statistical Tests for Comparing Accuracy of Spatial
Predictions (August)
Principal Components Analysis for Binary Data (May)
Deconvolution in Random Effects Models via Normal
Mixtures (August)
Choosing a Kernel for Cross-Validation (August)
Model-Based Pre-Processing in Protein Mass
Spectrometry (December)
On Parametric and Nonparametric Methods for
Dependent Data (August)
Bayesian Semiparametric and Models for
Heterogeneous, Cross-Platform Differential Gene
Expression (December)
Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product
Diffusion (August)
Bayesian model Selection for High-Dimensional HighThroughput Data (May)
Nonparametric Methods for Point Processes and
Geostatistical Data (August)
Bayesian Nonparametric Methods for Protein Structure
Prediction (August)
Coherent Control of Laser Field and Spectroscopy in
Dense Atomic Vapor (May)
Multivariate Skew-t Distributions in Econometrics and
Environmetrics (December)
An Addictive Bivariate Hierarchical Model for Functional
Data and Related Computations (August)
Resampling Methodology in Spatial Prediction and
Repeated Measures Time Series (December)
Bias Reduction and Goodness-of-Fit Tests in Conditional
Logistic Regression Models (August)
Secondary Analysis of Case-Control Studies in Genomic
Contexts (August)
Population SAMC, ChIP-chip Data Analysis and Beyond
(December)
Bayesian Methods in Nutrition Epidemiology and
Regression-Based Predictive Models in Healthcare
(December)
Extended Homozygosity Score Test to Detect Positive
Selection in Genome-Wide Scans (May)
Mallick, B.
Genton, M.
Lee, Seokho
Litton, Nathaniel
Savchuk, Olga
Wagaman, John C.
Bandyopadhyay,
Soutir
Dhavala, Soma Sekhar
Hartman, Brian M.
Joshi, Adarsh
Kolodziej, Elizabeth Y.
2010
Lennox, Kristin P.
Lindsey, Charles D.
Marchenko, Yulia
Redd, Andrew M.
Rister, Krista Dianne
Sun, Xiuzhen
Wei, Jiawei
Wu, Mingqi
Zhang, Saijuan
Zhong, Ming
Huang/Carroll
Hart, J.
Hart/Sheather
Huang/West
Lahiri, S
Mallick, B.
Mallick, B.
Dahl/Johnson
Sherman, M.
Dahl, D.
Sheather, S.
Genton, M.
Carroll, R.
Lahiri, S.
Wang/Sinha
Carroll, R.
Liang, F.
Carroll/Huang
Fan, R.
65
Barney, Bradley J.
Chen, Lianfu
Chen, Nai-Wei
Garcia, Tanya Pamela
Glab, Daniel L.
2011
Jin, Ick Hoon
Konomi, Bledar
Maadoliat, Mehdi
Mondal, Anirban
Pan, Huijun
Singh, Trijya
Sun, Ying
Talluri, Rajesh
Wang, Qi
Xu, Ganggang
Crawford, Scott
2012
Jann, Dominic A.
Kim, Mi Jeong
Kohli, Priya
Lee, Jun B.
Park, Jincheol
Wang, Xuan
Xun, Xiaolei
Zhan, Dongling
Zhang, Lin
Bayesian Joint Modeling of Binomial and Rank Response
Data (August)
Topics on Regularization of Parameters in Multivariate
Linear Regression (December)
Goodness-of-Fit Tests Issues in Generalized Linear Mixed
Models (December)
Efficient Semiparametric Estimators for Biological, Genetic,
and Measurement Error Applications (August)
Testing Lack-of-Fit of Generalized Linear Models via
Laplace Approximation (May)
Statistical Inferences for Models with Intractable
Normalizing Constants (August)
Bayesian Spatial Modeling of Complex and High
Dimensional Data (December)
Dimension Reduction and Covariance Structure for
Multivariate Data, Beyond Gaussian Assumption (August)
Bayesian Quantification for Large Scale Spatial Inverse
Problems (August)
Bivariate B-Splines and Its Application in Spatial Data
Analysis (August)
Efficient Small Area Estimation in the Presence of
Measurement Error in Covariates (August)
Inference and Visualization of Periodic Sequences (August)
Bayesian Gaussian Graphical Models Using Sparse
Selection Priors and Their Mixtures (August)
Frequent-Bayes Goodness-of-Fit Tests (August)
Variable Selection and Function Estimation Using
Penalized Methods (December)
Efficient Estimation in a Regression Model with Missing
Responses (August)
Bayesian Logistic Regression with Jaro-Winkler String
Comparator Scores Provides Sizable Improvement in
Probabilistic Record Matching (December)
Efficient Semiparametric Estimators for Nonlinear
Regressions and Models under Sample Selection Bias
(August)
Prediction and Estimation of Random Fields (August)
A Novel Approach to the Analysis of Nonlinear Time Series
with Applications to Financial Data (May)
Bayesian Analysis for Large Spatial Data (August)
Statistical Methods for the Analysis of Mass SpectrometryBased Proteomics Data (May)
Statistical Inference in Inverse Problems (May)
The k-Sample Problem When k is Large and n Small (May)
Application of Bayesian Hierarchical Models in Genetic
Data Analysis (December)
Johnson/Sheather
Pourahmadi, M.
Wehrly, T.
Ma, Y.
Wehrly, T.
Liang, F.
Mallick/Sang
Huang, J.
Mallick, B.
Huang/Zhou
Carroll/Wang
Hart/Genton
Mallick, B.
Hart, J.
Huang/Wang
Müller-Harknett, U.
Speed/Sheather
Ma, Y.
Pourahmadi/Chen
Subba Rao, S.
Liang, F.
Dabney, A.
Mallick/Carroll
Hart, J. D.
Mallick/
Baladandayuthapani
66
Ball, Robyn L.
Chen, Hsiang-Chun
2013
Cheng, Yichen
Gaucher, Beverly J.
Mukhopadhyay,
Subhadeep
Wang, Yiyi
Xu, Kun
Zhu, Xinxin
Chown, Justin Andrew
De, Debkumar
Feng, Shuo
Gregory, Karl Bruce
Kim, Jinsu
2014
Lin, Fang-Yu
Lu, Ming
Miao, Jiangang
Qu, Yuan
Roh, Soojin
Sarkar, Abhra
Song, Qifan
Sun, Rayne
Wang, Yanqing
Statistical Methods for High Dimensional Biomedical Data
(May)
Interference for Clustered Mixed Outcomes from a
Multivariate Generalized Linear Mixed Model (August)
Stochastic Approximation and Its Application in MCMC
(August)
Factor Analysis for Skewed Data and Skew-Normal
Maximum Likelihood Factor Analysis (May)
Nonparametric Inference for High Dimensional Data (May)
Statistical Models for Next Generation Sequencing Data
(May)
Semiparametric Estimation and Inference with MisMeasured, Correlated or Mixed Observations, and the
Application in Ecology, Medicine, and Neurology
(December)
Wind Speed Forecasting for Power System Operation
(August)
New Approaches in Testing Common Assumptions for
Regressions with Missing Data (August)
Essays on Bayesian Time Series and Variable Selection
(May)
A Likelihood Based Framework for Data Integration with
Application to eQTL Mapping (August)
Two-Sample Testing in High Dimension and a Smooth
Block Bootstrap for Time Series (August)
A Bootstrap Metropolis-Hastings Algorithm for Bayesian
Analysis of Big Data (December)
Combining Strategies for Parallel Stochastic
Approximation Monte Carlo Algorithm of Big Data
(December)
Investigation of Simple Linear Measurement Error Models
(SLMEMS) with Correlated Data (December)
New Advances in Logistic Regression for Handling Missing
and Mismeasured Data with Applications in Biostatistics
(August)
Estimation of Large Spectral Function and Its Application
(August)
Robust Ensemble Kalman Filters and Localization for
Multiple State Variables (August)
Bayesian Semiparametric Density Deconvolution and
Regression in the Presence of Measurement Errors
(August)
Variable Selection for Ultra-High Dimensional Data
(August)
Thresholding Multivariate Regression and Generalized
Principal Components (May)
Relative Risks Analysis in Nutritional Epidemiology
(August)
Dabney, A.
Wehrly, T.
Liang, F.
Hart/Wehrly
Lahiri/Parzen
Dahl/Liang
Ma, Y.
Sang/Genton
Müller-Harknett, U.
Liang/Mallick
Huang, J.
Carroll/Lahiri
Liang, F.
Liang/Carroll
Dahm, P.F.
Wang/Sinha
Huang, J.
Jun/Genton
Mallick/Carroll
Liang, F.
Pourahmadi/Carroll
Carroll/Mallick
67
Wei, Rubin
Highly Nonlinear Measurement Error Models in Nutritional
Epidemiology (May)
Carroll, R.
68
Ph.D. Graduate Employers 2009-2014
2011
2010
2009
Student
Gosh, Souparno
Herring, Amanda Scott
Lee, Seokho
Litton Nathaniel
Savchuk, Olga
Wagaman, John
Bandyopadhyay, Soutir
Dhavala, Soma Sekhar
Hartman, Brian
Joshi, Adarsh
Kolodziej, Elizabeth Y.
Lennox, Kristin
Lindsey, Charles D.
Marchenko, Yulia
Redd, Andrew M.
Rister, Krista Dianne
Sun, Xiuzhen (Jenny)
Wei, Jiawei
Wu, Mingqi
Zhang, Saijuan
Zhong, Ming
Barney, Bradley
Chen, Lianfu
Chen, Nai-Wei
Garcia, Tanya
Glab, Daniel L.
Job Title
Assistant Professor
Assistant Professor
Lecturer
Manager of Statistical Analysis
Visiting Instructor
Assistant Professor
Assistant Professor
Associate Research Scientist
Assistant Professor
Manager, Biostatistics (Oncology Biomarkers)
Senior Lecturer
Statistician
Senior Statistician, Software Developer
Associate Director of Biostatistics
Assistant Professor
Senior Statistician
Research Assistant Professor
Statistical Methodologist
Statistician
Biometrician
Principal Statistician
Assistant Professor
Quantitative Statistics Analyst
Biostatistics Statistical Consultant
Assistant Professor
Postdoctoral Trainee
Employer
Texas Tech University
Colorado School of Mines
Korea University of Foreign Studies
Capital One Auto Finance
University of South Florida
Western Carolina University
Lehigh University
Dow AgroSciences LLC, Global Research Center
University of Connecticut
Gilead Sciences
Texas A&M University, Statistics
Lawrence Livermore National Laboratory
StataCorp
StataCorp
University of Utah
Capital One
Boston Medical Center
Novartis
Shell Global Solutions
Merck
Capital One
Kennesaw State University
Sakonnet Technology
University of Texas Medical Branch at Galveston
Texas A&M University, Biostatistics
Mexican American & US Latino Rsch. Ctr, Texas A&M
69
2012
2013
Jin, Ick Hoon
Konomi, Bledar (Alex)
Maadodiat, Mehdi
Mondal, Anirban
Pan, Huijun
Singh, Trijya
Sun, Ying
Talluri, Rajesh
Wang, Qi
Xu, Ganggang
Crawford, Scott
Jann, Dominic A.
Kim, Mi Jeong
Kohli, Priya
Lee, Jun B.
Park, Jincheol
Wang, Xuan
Xun, Xiaolei
Zhan, Dongling
Zhang, Lin
Ball, Robyn L.
Chen, Hsiang-Chun
Cheng, Yichen
Gaucher, Beverly J.
Mukhopadhay, Subhadeep
Wang, Yiyi
Xu, Kun
Zhu, Xinxin
Research Scientist
Assistant Professor
Assistant Professor
Assistant Professor
Sr. Consultant, Claim Analytics
Assistant Professor
Assistant Professor
Postdoctoral Fellow, Biostatistics
Group Model Variation
Assistant Professor
Academic Professional Lecturer
Senior Associate Analytic Engineer
Senior Engineer
Assistant Professor of Mathematics
Quantitative Analyst
Postdoctoral Fellow
Research Statistical Analyst
Senior Biometrician
Assistant Director
Assistant Professor
Postdoctoral Associate
Research Statistical Analyst
Postdoctoral Researcher
Mathematical Statistician
Assistant Professor
Director, Home Office Claims
Postdoctoral Associate
Statistical Modeler
Ohio State University, Center for Biostatistics
University of Cincinnati
Marquette University
Case Western Reserve University
Travelers Insurance
Le Moyne College
King Abdullah University of Science & Technology
UT- MD Anderson Cancer Center
Standard Chartered Bank
Binghamton University, State University of New York
University of Wyoming
SAS Institute
Samsung Electronics
Connecticut College
CLS Group
Ohio State University, Stat & Math Bioscience Inst.
UT-MD Anderson Cancer Center
Novartis
Data & Research Services, Texas A&M University
University of Minnesota
The Jackson Laboratory
MD Anderson Cancer Center
Fred Hutchinson Cancer Research Center
USDA, National Agricultural Statistics Service
Temple University
Liberty Mutual Insurance
University of Miami
LexisNexis Group
70
2014
Chown, Justin Andrew
De, Debkumar
Feng, Shuo
Gregory, Karl Bruce
Kim, Jinsu
Lin, Fang-Yu
Lu, Ming
Miao, Jiangang
Qu, Yuan
Roh, Soojin
Sarkar, Abhra
Song, Qifan
Sun, Rayne
Wang, Yanqing
Wei, Rubin
Postdoctoral Researcher
Research Intern
Statistician/Scientist II
Postdoctoral Researcher
Enterprise Solution Specialist
AVP, Risk Modeler
Searching for industry position
Senior Data Analyst
Visiting Assistant Professor
Searching for industry position
Postdoctoral Associate
Assistant Professor
AVP, Corp. Investment Quan. Finance Analyst
Postdoctoral Researcher
Senior Statistician
Université catholique de Louvain
Echelon Capital Strategies, LLC
Ceva Biomune
University of Mannheim
LG CNS Co., Ltd.
JP Morgan Chase
American International Group, Inc.
Purdue University
Duke University
Purdue University
Bank of America
Fred Hutchinson Cancer Center
Eli Lilly & Company
71
III.
FACULTY INFORMATION
72
Department of Statistics Faculty, 2014-2015
V. E. Johnson, Professor and Head; Ph.D. in Statistics: University of Chicago, 1989; longitudinal
data, nonparametric statistics, applied statistics, biostatistics, categorical data, Bayesian methods.
M. T. Longnecker, Professor and Associate Head; Ph.D. in Statistics: Florida State University, 1976;
statistical education and consulting.
D. Akleman, Senior Lecturer; Ph.D. in Agricultural Economics: Texas A&M University, 1996;
time series, stochastic processes, risk analysis, artificial intelligence, econometrics.
A. Bhattacharya, Assistant Professor; Ph.D. in Statistics: Duke University, 2012; Factor models,
Gaussian process, high-dimensional data, large contingency tables.
J. H. Carroll, Senior Lecturer; MS in Statistics: Texas A&M University, 1990; Statistics education.
R. J. Carroll, Distinguished Professor; Ph.D. in Statistics: Purdue University, 1974; longitudinal
data, measurement error, nutritional epidemiology, bioinformatics.
W. Chen, Professor; Ph.D. in Statistics: New York University, 2001; long memory time series,
econometrics
D. B. H. Cline, Professor; Ph.D. in Statistics: Colorado State University, 1983; Stochastic
networks, nonlinear time series, ergodicity, Markov chains, distribution tails, regular variation
A. Dabney, Associate Professor; Ph.D. in Biostatistics: University of Washington, 2006;
microarrays, bioinformatics, classification methods.
P. F. Dahm, Professor and Graduate Advisor; Ph.D. in Statistics: Iowa State University, 1979;
measurement error models, biostatistics, econometrics.
C. E. Gates, Professor Emeritus; Ph.D. in Experimental Statistics: North Carolina State
University, 1955; design and analysis of experimental data, estimation of wildlife abundance and
modeling non-linear growth curves.
J. D. Hart, Professor; Ph.D. in Statistics: Southern Methodist University, 1981; nonparametric
function estimation, time series, bootstrap methods.
K. Hatfield, Lecturer; MBA in Operations Research: North Texas State University, 1980;
Statistics education and consulting.
R. R. Hocking, Professor Emeritus; Ph.D. in Statistics: Iowa State University, 1962; regression,
mixed models and multivariate analysis.
J. Huang, Professor; Ph.D. in Statistics: University of California, Berkeley, 1997; nonparametric
and semiparametric methods, statistical function estimation using polynomial splines, statistical
methods for longitudinal data/panel data, multivariate/functional data analysis, survival analysis,
duration data, event history analysis, statistics application in business.
73
O. C. Jenkins, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1972; statistical
sampling and experimental design.
E. R. Jones, Executive Professor, Ph.D. in Statistics: Virginia Polytechnic and State University,
1976; applied statistics, statistical computing, data mining/machine learning.
M. Jun, Associate Professor, Ph.D. in Statistics: University of Chicago, 2005; statistical
methodologies, environmental problems, space-time covariance modeling, numerical model
evaluation in air quality problems, combining numerical model output with observed data.
M. Katzfuss, Assistant Professor, Ph.D. in Statistics: Ohio State University, 2011; Spatial and
spatio-temporal statistics, Bayesian inference, massive datasets, probabilistic forecasting,
applications to environmental data.
E. Y. Kolodziej, Senior Lecturer, Ph.D. in Statistics: Texas A&M University, 2010; spatial
statistics, statistics education, consulting.
H. C. Liang, Senior Lecturer, Ph.D. in Statistics: University of New Mexico, 2003; Linear models,
statistical education, undergraduate research.
J. P. Long, Assistant Professor, Ph.D. in Statistics: University of California, Berkeley, 2013;
Applied statistics, machine learning, time series, classification, astrostatistics, errors-in-variables.
B. Mallick, Distinguished Professor; Ph.D. in Statistics: University of Connecticut, 1994;
Bayesian hierarchical modeling, nonparametric regression and classification, bioinformatics,
spatio-temporal modeling, machine learning, functional data analysis, Bayesian nonparametrics,
petroleum reservoir characterization, uncertainty analysis of computer model outputs.
J. H. Matis, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1970;
biomathematics, compartmental analysis, statistical ecology and applied stochastic processes.
U. Müller-Harknett, Professor; Ph.D. in Mathematics: University of Bremen, 1997; non- and
semi-parametrics, efficient estimation.
H. J. Newton, Professor and Dean; Ph.D. in Statistics: State University of New York at Buffalo,
1975; time series analysis, computational statistics.
E. Parzen, Distinguished Professor Emeritus; Ph.D. in Mathematics: University of California
(Berkeley), 1953; statistical science-developing statistical methods for time series analysis, data
analysis, and change analysis.
M. Pourahmadi, Professor, Ph.D. in Statistics: Michigan State University, 1980, time series
analysis and prediction theory, multivariate analysis, longitudinal data analysis, mixed-effects
models, data mining, stochastic volatility models.
L. J. Ringer, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1966; applied
statistics, survey sampling and reliability.
H. Sang, Associate Professor, Ph.D. in Statistics: Duke University, 2008; Bayesian statistics with
focus on spatial and spatio-temporal statistics.
74
H. Schmiediche, Director of Information Technology; Ph.D. in Statistics: Texas A&M
University, 1993; computational statistics.
S. J. Sheather, Professor and Academic Director of MS Analytics & Online Programs; Ph.D. in
Statistics: LaTrobe University, 1986; development of regression diagnostics and robust and
flexible regression methods, statistical models of wine quality.
M. Sherman, Professor; Ph.D. in Statistics: University of North Carolina at Chapel Hill, 1992;
biostatistics, spatial statistics.
S. Sinha, Associate Professor, Ph.D. in Statistics: University of Florida, 2004; methodological
research: missing data technique, measurement error, splines, Bayesian methods: parametric and
nonparametric methods, application: epidemiology, genetic epidemiology.
W. B. Smith, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1967; multivariate
analysis, missing data methods, correspondence analysis.
F. M. Speed, Professor Emeritus; Ph.D. in Statistics: Texas A&M University, 1969;
computational statistics, biostatistics, linear models, applied statistics, multivariate methods,
environmental and industrial statistics, teaching statistics real time.
C. H. Spiegelman, Distinguished Professor; Ph.D. in Statistics & Applied Mathematics:
Northwestern University, 1976; calibration curves, measurement error models, applied statistics,
especially to chemistry.
S. Subba Rao, Associate Professor; Ph.D. in Statistics: University of Bristol, UK, 2001; time
series, nonstationary processes, nonlinear processes, recursive online algorithms, spatio-temporal
models.
E. Toby, Professor Emerita; Ph.D. in Mathematics: University of California, San Diego, 1988;
biostatistics, diffusions processes.
S. Wang, Professor; Ph.D. in Statistics: University of Texas at Austin, 1988; biostatistical
inferences, missing and mis-measured data modeling and analysis, non- and semi-parametric
methodology, resampling methods, small sample asymptotics, survey sampling.
T. E. Wehrly, Professor; Ph.D. in Statistics: University of Wisconsin, 1976; stochastic models,
directional data, mathematical statistics, nonparametric function estimation.
L. Zhou, Associate Professor, Ph.D. in Statistics: University of California, 1997; statistical
Methodology and application in bioinformatics, nutrition and epidemiology,
functional/longitudinal data analysis.
J. Zinn, Professor of Mathematics and Statistics; Ph.D. in Mathematics: University of Wisconsin,
1972; empirical processes, bootstrapping.
75
76
77
78
79
Honors & Awards Received by Faculty
YEAR
2009
NAME
A. Dabney
M. Longnecker
AWARD
Montague Scholar, Center for Teaching Excellence
Elected Fellow, American Statistical Association
2010
R. Carroll
E. Toby
Oderoff Lecture, University of Rochester
Distinguished Achievement Award – Teaching, Association of
Former Students
2011
A. Dabney
Distinguished Achievement Award – Teaching, The
Association of Former Students
Statistics Education Award, Mu Sigma Rho
12th Man Award
M. Longnecker
M. Speed
2012
R. Carroll
S. Sheather
T. Wehrly
2013
R. Carroll
J. Huang
B. Mallick
H. Newton
S. Sheather
S. Wang
J. Hart
2014
J. Calvin
R. Carroll
F. Dahm
C. Spiegelman
E. Toby
Honorary Doctorate, Institut de Statistique, Universite
Catholique de Louvain
Namesake, Fish Camp
12th Man Award
Fellow, American Association of the Advancement of Science
Fellow, Institute of Mathematical Statistics
Fellow, American Statistical Association
Fellow, American Association for the Advancement of Science
Fellow, American Association for the Advancement of Science
Distinguished Achievement Award – Teaching, The
Association of Former Students
12th Man Award
Visiting Fellowship Award, Australian National University
Mathematical Sciences Research
12th Man Award
Professor Emeritus of Statistics
Inaugural Holder of the Jill and Stuart A. Harlin ’83 Chair in
Statistics
Gottfried E. Noether Senior Scholar Award
12th Man Award
Member of the Houston Forensic Science Local Government
Corporation
Fellow to American Association for the Advancement of
Science
Professor Emerita of Statistics
80
Department of Statistics
2014-2015 Committee Assignments
COMMITTEE
Department Head
Associate Head
Admissions Committee
Advisory Committee
CHAIR
Johnson
Longnecker
Huang
Longnecker
Assistantship Duties
Awards
Bioinformatics
Colloquia-Special Events
Computing
Consulting Center
Diversity
Endowed Positions Committee
Examinations (Masters)
Faculty Recruiting
Longnecker
R. Carroll
Mallick
Bhattacharya
Schmiediche
Jones
Akleman
Sheather
Longnecker
Hart
Graduate Curriculum Committee
Huang
Graduate Service
Graduate Admissions Committee
Graduate Committee
Pourahmadi
Huang
Huang
Grant Opportunities
Library
NISS
Promotion & Tenure Committee
Spiegelman
Long
Spiegelman
Chen
Public Relations/Magazine
SECC Representative
SRCOS Representative
Student Evaluation Committee
Johnson
Johnson
Johnson
Sherman
Teaching Assignments
Tenure & Promotion
Longnecker
Chen
Undergraduate Minors
Wehrly
Undergraduate Service
Undergraduate Committee
J.H. Carroll
Wehrly
Website Committee
Schmiediche
MEMBERS
Mallick, Jun, Wehrly
Akleman, Hart, Huang,
Katzfuss, Johnson, Jun,
Sheather, Mueller-Harknett
J.H. Carroll
Mallick, Spiegelman
Dabney, Sinha, Zhou
Sinha
Spiegelman, Johnson, Mallick
Johnson, Katzfuss, MuellerHarknett, Jun, Sang
Longnecker, Cline, Subba Rao,
Mueller-Harknett, Bhattacharya
Zhou, Wehrly
Mallick, Jun, Wehrly
Mallick, Cline, Dahm,
Longnecker, Sinha, Jun, Wang
Subba Rao
Pourahmadi, Wang, R. Carroll,
Mueller-Harknett, Jun, Sherman
Mueller-Harknett, Chen, Sinha,
Subba Rao, Jun, Bhattacharya,
Wang
R. Carroll, Jun, MuellerHarknett, Sherman, Wang,
Pourahmadi
Dabney, Hatfield, Kolodziej,
Toby, Johnson, Sang, Dahm
Longnecker
Dabney, Hatfield, Kolodziej,
Toby, Johnson, Sang, Liang
Longnecker, Sang, Katzfuss
81
FACULTY EDITORIAL SERVICE
Bhattacharya, Anirban
Reviewer: Annals of Applied Statistics, Annals of Statistics, Bayesian Analysis, Bernoulli, Biometrika,
Electronic Journal of Statistics, Journal of the American Statistical Association, Journal of Machine Learning
Research
Chen, Willa
Editorial Board Member: Journal of the American Statistical Association – T&M (2014-Present)
Journal of Computational and Graphical Statistics (2009-Present)
Electronic Journal of Statistics (2010-2013)
Journal of the American Statistical Association – A&CS (2009-2012)
Cline, Daren
Reviewer: Econometric Theory, Bernoulli, Stochastic Process and their Applications, Biometrika,
ASCE Journal of Transportation Engineering, Electronic Journal of Statistics, Statistics and Probability Letters,
Annals of Statistics, Journal of Difference Equations and Applications, Extremes, Journal of the American
Statistical Association, Statistical Methodology, Cogent Mathematics
Dahm, P. Fred
Reviewer: Agronomy Journal, American Journal of Public Health, American Statistician, Biometrics,
Communications in Statistics, IEEE Transactions on Communications, Journal of the American Statistical
Association, Psychometrika, Statistics and Probability Letters, Statistics in Medicine, Technometrics, Western
Journal of Agricultural Economics
Hart, Jeff
Editorial Board Member: Journal of the American Statistical Association (2008-2011, 1996-2002)
Huang, Jianhua
Editorial Board Member: STAT—The ISI’s Journal for the Rapid Dissemination of Statistics Research
(2015-Present)
Johnson, Valen
Co-Editor: Bayesian Analysis (2010-2014)
Associate Editor: Journal of the American Statistical Association (1992-1996, 2011-Present)
Bayesian Analysis (2006-2010)
Jones, Edward R.
Editorial Board Member: Journal of the American Statistical Association (2014-Present)
Journal of Business and Economics Statistics (2012-Present)
Statistics and Probability Letters (2008-2014)
Jun, Mikyoung
Editorial Board Member: STAT, (2012-Present)
Journal of Agricultural, Biological, and Environmental Statistics (JABES) (2011-Present)
Journal of the Korean Statistical Society (2008-Present)
Katzfuss, Matthias
Reviewer: Journal of Computational and Graphical Statistics, Journal of Computational and Graphical Statistics,
Annals of Applied Statistics, Biometrics
82
Kolodziej, Elizabeth
Book Review: Resampling Methods, Journal of the American Statistical Association
Liang, Hwa Chi
Editorial Board Member: Missouri Journal of Mathematical Sciences (2013-Present)
Long, James
Reviewer: Journal of the American Statistical Association, The Astrophysical Journal, Astronomy and
Computing, Astronomy and Astrophysics
Mallick, Bani
Editorial Board Member: Journal of Computational and Graphical Statistics (2004-Present)
Biostatistics (2009-Present)
SIAM/ASA Journal on Uncertainty Quantification (2013-Present)
Chemometrics (2013-Present)
Journal of Applied Mathematics and Stochastic Analysis (2005-2009)
Müller-Harknett, Ursula
Editorial Board Member: Statistics and Probability Letters (2011-present).
Pourahmadi, Mohsen
Editorial Board Member: Journal of the American Statistical Association (2014-Present)
Journal of Business and Economics Statistics (2012-Present)
Statistics and Probability Letters (2008-2014)
Electronic Journal of Statistics (2010-2012)
Journal of Applied Mathematics and Stochastic Analysis (2005-2009)
Sang, Huiyan
Editorial Board Member: STAT (2013-Present)
Sherman, Michael
Editorial Board Member: Journal of the American Statistical Association (2005-2014)
Sinha, Samiran
Reviewer: Biological Psychiatry, Biometrics, Communication of Statistics, Computational Statistics and Data
Analysis, Electronic Journal of Statistics, Journal of Applied Statistics, Journal of the American Statistical
Association, Journal of Multivariate Analysis, Journal of the Nonparametric Statistics, Journal of the Royal
Statical Society, Series B, Journal of the Statistical Planning and Inference, SCIENCE CHINA Mathematics,
Stat, Statistics and its Interface, Statistics in Medicine
Spiegelman, Cliff
Editorial Board Member: JASA (one month as acting T&M editor), Environmetrics, Journal of
Chemometrics, Journal of Proteomics, Journal of Transportation Statistics, Journal of Transportation and Statistics
Subba Rao, Suhasini
Editorial Board Member: Statistics (2012-Present)
Wang, Suojin
Editor-in-Chief: Journal of Nonparametric Statistics (2007–2012)
83
Editorial Board Member: Biometrics (1997–2005)
InterStat (1995–2009)
Journal of Nonparametric Statistics (2004–2007, 2013–Present)
Statistics & Probability Letters (2014–Present)
Wehrly, Tom
Statistics and Probability Letters (1982–2007)
Zhou, Lan
Reviewer: An International Journal, Annals of Applied Statistics, Biometrics, Biostatistics, Canadian Journal of
Statistics, Computational Statistics and Data Analysis, Electronic Journal of Statistics, Journal of American
Statistical Association, Journal of Computational and Graphical Statistics, Journal of Machine Learning Research,
Journal of Nonparametric Statistics, Journal of Statistical Computation and Simulation, Journal of Statistical
Planning and Inference, Journal of Statistical Theory and Practice, Life Data Analysis, Scandinavian Journal of
Statistics, Statistical Applications in Genetics and Molecular Biology, Statistica Sinica
84
Primary Investigator Awards 2006-2013
Name
Carroll, R. J.
Chen, W. W.
Cline, D. B.
Dabney, A. R.
Years
2005-2008
2005-2013
2007-2008
2008-2011
2012-2013
Granting Agency
National Aeronautics and Space
NIH - Training Grant
Baylor College of Medicine
University of Alabama
California Table Grape Comm.
Role
PI
PI
PI
PI
PI
Direct
$527,245
$3,200,954
$21,023
$150,004
$2,126
Indirect
$44,835
$199,464
$9,565
$5,472
$106*
Total
$572,080
$3,400,418
$30,588
$155,476
$2,232
2006-2007
PI
$42,405
$19,930*
$62,335
2006-2010
2010-2013
NSF - Fractional Cointegration
NSF - Long Memory Time
Series
NSF-Restriciton Likelihood
PI
PI
$89,250
$119,682
$40,610
$55,653
$129,860
$175,335
2013-2016
NSF - NeTS Small
PI
$10,523
$4,946*
$15,469
2008-2011
PI
$422,846
$198,738*
$621,584
2008-2012
2008-2011
2008-2011
2010-2011
2011-2013
2011-2013
2012
2013-
Battelle Labs
Dept of Health and Human
Svcs
Pacific Northwest Natl Labs
American Inst. For Cancer Res.
Pacific Northwest Natl Labs
Natl Inst of Food and Agri.
NIH - Epigenetics of the Aging
National Aeronautics and Space
American Cancer Society
PI
PI
PI
PI
PI
PI
PI
PI
$276,320
$427,528
$76,835
$194,195
$2,362,466
$312,501
$8,712
$179,500
$125,727
$200,938*
$36,112*
$91,272*
$338,887
$138,966
$4,095*
$84,365*
$402,047
$628,466
$112,947
$285,467
$2,701,353
$451,467
$12,807
$263,865
2006-2010
NSF - Cluster-Based
Bootstrapping
PI
$77,129
$35,538
$112,667
2011-2013
NSF-New Method for
Estimating Random Effects
PI
$100,040
$43,932
$143,972
2006-2009
2009-2013
2012-2013
2013-
Collaborative Research Statistical Learning
Conf. on Statistical Methods
NSF - Collaborative Research
Department of Defense
PI
PI
PI
PI
$69,581
$18,407
$85,476
$101,672
$29,402
$8,651*
$27,852
$47,786*
$98,983
$27,058
$113,328
$149,458
Hart, J. D.
Huang, J.
85
Name
Years
2012-2013
Granting Agency
NIH - Consistent Model
Selection
UTMDCC - Reducing
Symptom
2009-2012
2012-2013
NSF - Nonstationary Spatial
NSF - In-depth Development
PI
PI
$51,148
$103,126
$23,784
$42,050
$74,932
$145,176
2012-2013
US Dept of Agriculture
PI
$36,752
$17,274
$54,026
2002-2006
NSF - Bayesian Nonlinear
Regression
PI
$21,977
$7,859
$29,836
2009-2011
NSF - ATD: Bayesian Data
Missing
PI
$301,579
$53,821
$355,400
2012-2013
UTMDACC - Education
Experience Program
PI
$53,105
n/a
$53,105
2009-2012
NSF - Efficient Estimation in
Semiparametric Regression
PI
$80,525
$37,445
$117,970
2009-2011
NSF - Generalized Linear
Models
PI
$139,260
$55,473
$194,733
PI
$66,887
$11,082
$77,969
PI
$81,931
$35,124
$117,055
PI
$532,827
$250,429*
$783,256
PI
$75,000
$35,250*
$110,250
UTMDACC - Education
Experience
PI
$33,142
n/a
$33,142
NIH - Fetal Alcohol Exposure
NIH - Fetal Alcohol Exposure
PI
PI
$32,357
$357,171
$15,208*
$148,211
$47,565
$505,382
2012-2016
Johnson, V. E.
Jun, M.
Longnecker, M.
Mallick, B.
Mueller-Harknett,
U.
Pourahmadi, M.
2007-2008
2007-2008
Sheather, S. J.
2007-2008
2012-2013
2012
Sherman, M.
2001-2006
2006-2013
Dept. Of Health and Human
Svc.
Dept. Of Health and Human
Svc.
NIH - Development of a
Controlled Hemorrhage
NSF - Texas Census Research
Ctr.
Role
Direct
Indirect
Total
PI
$812,992
$310,708
$1,123,770
PI
$17,720
$3,281
$21,001
86
Name
Sinha, S.
Subba Rao, S.
Wang, S.
Wehrly, T.
Zhou, L.
Years
2010-2011
Granting Agency
DOE - Thirteenth North
American Meeting of New
Researchers
Role
Direct
Indirect
Total
PI
$12,665
n/a
$12,665
2010-2012
NIH - North American Meeting
of New Researchers
PI
$27,962
n/a
$27,962
2010-2013
2013-2015
NSF - Collaborative Research:
Statistics Methods
NCI - Innovative Approaches
PI
PI
$29,981
$57,871
$13,942
$27,199*
$43,923
$85,070
2008-2012
NSF - Beyond Stationarity
PI
$124,312
$14,422
$138,734
2011-2013
NSF - Fourier Methods in the
Analysis of Non-Stationary
PI
$89,833
$39,303
$129,136
2006-2009
NIH - Health Maintenance
Consortium
PI
$177,575
$83,460*
$261,035
2003-2006
University of N. Carolina - Long
Term Care Needs
PI
$33,811
$15,891*
$49,702
2007-2012
2008-2012
NIH - Program for Rural and
Minority Health Disparity
Baylor College of Medicine
PI
PI
$2,996,480
$193,724
$1,408,346*
$80,093
$4,404,826
$273,817
2008-2013
2009-2011
Robert Wood Johnson
Foundation
Natl Inst of Mental Health
PI
PI
$438,836
$499,543
$53,617
$234,785*
$492,453
$734,328
2006-2011
NSF - Integrated Undergraduate
PI
$185,068
$13,894
$198,962
2009-2013
NSF - Statistics Methods for
Complex Functional Data
Pi
$206,362
$88,130
$294,492
*Indirect costs estimated
87
Co-Principal and Collaborating Investigator Awards 2006-2013
(Please note that award totals in some instances refer to total grant amount, not amount received by
individual collaborating investigators)
Name
Years
2005-2006
Carroll, R.
Dabney, A. R.
Hart, J. D.
Huang, J.
Jun, M.
Granting Agency
National Institute for
Environmental Health
Role
Direct
Indirect
Total
Co-PI
$34,025
$28,849
$62,874
Co-PI
Co-PI
Co-PI
Co-PI
$57,630
$451,740
$5,560
$14,849
$26,221
$203,712
$278*
$6,979*
$83,851
$655,452
$5,838
$21,828
Co-PI
Co-PI
Co-PI
$142,819
$3,915,206
$56,285
$27,249
$1,200,000
$26,454*
$170,068
$5,115,206
$82,739
2009-2013
2010-2013
2012-2013
NIH - Bayesian Models for
Gene Express
NIH - Measurement Error
NSF - Beowulf Cluster
NSF - Cluster Computing
NSF - Bayesian Data
Missing
KAUST - IAMCS
Columbia University
2010-2013
National Science
Foundation
Co-PI
$90,900
$3,846
$94,746
2006-2007
NSF - Beowulf Cluster
Co-PI
$5,560
$278*
$5,838
2010-2013
NSF - A New Approach of
Statistical Modeling
Co-PI
$109,553
$10,694
$120,247
2010-2011
2011-2013
NSF - Conf. on Resampling
Methods
KAUST - IAMCS
Co-PI
Co-PI
$4,986
$581,873
$2,343*
$273,480*
$7,329
$855,353
2008-2010
2011-2013
NSF - CMG Research
KAUST - IAMCS
Co-PI
Co-PI
$81,790
$581,873
$31,882
$273,480*
$113,672
$855,353
2005-2009
2005-2013
2006-2007
2009-2011
88
Name
Mallick, B. K.
Newton, H. J.
Sang, H.
Sheather, S. J.
Wang, S.
Years
Granting Agency
Role
Direct
Indirect
Total
2006-2009
2006-2013
NIH - Bayesian Models for Gene
Expression
NIH - Measurement Error
Co-PI
Co-PI
$233,863
$451,740
$106,408
$203,712
$340,271
$655,452
2001-2006
NIH - Nutrition, Biostatistics and
Bioinformatics
Co-PI
$18,490
$1,470
$19,960
2006-2007
NSF - CMG Research on Multiscale
Spatial Models
Co-PI
$55,443
$22,164
$77,607
2006-2010
2006-2007
NSF - CMG Research: Statistical
Analysis of Large Non-Gaussian
NSF - Beowulf Cluster
Co-PI
Co-PI
$174,430
$5,560
$67,944
$278*
$242,374
$5,838
2007-2009
2007-2011
2008-2013
2010-2013
2011-2013
NSF - A Unified Framework for
Statistical Modeling
NSF - Multiscale Data Integration
Lawrence Livermore Natl Labs
DOE - Bayesian Uncertainty
KAUST - IAMCS
Co-PI
Co-PI
Co-PI
Co-PI
Co-PI
$44,858
$324,267
$393,265
$357,162
$581,873
$21,083*
$121,788
$184,835*
$36,673
$273,480*
$65,941
$446,055
$578,100
$393,835
$855,353
2013-2016
DOE - Scalable Multilevel
Uncertainty Quantification
Co-PI
$6,811
$3,201*
$10,012
2006-2008
NSF - Noyce Scholarship
Co-PI
$43,970
$20,666*
$64,636
2007-2008
2007-2008
NSF - Center for the Appli. Of IT
in Teaching
Supplemental to the ITS Ctr.
Co-PI
Co-PI
$416,295
$22,101
$195,659*
$6,853
$611,954
$28,954
2010-2013
2011-2013
NSF - A New Approach of
Statistical Modeling
KAUST - IAMCS
Co-PI
Co-PI
$109,533
$581,873
$10,694
$273,480*
$120,227
$855,353
2009-2013
NIH - Lipoprotein Density
Co-PI
$326,753
$66,822
$393,575
2006-2007
NSF-Beowulf Cluster
Co-PI
$5,560
$278*
$5,838
*Indirect costs estimated
89
Faculty Collaborations within Texas A&M
Raymond Carroll
Nutrition and Food Science
Daren Cline
Computer Science and Engineering
Industrial and Systems Engineering
Alan Dabney
Nutrition and Food Science
Neuroscience and Experimental Therapeutics
Mathematics
Genetics
Jeffrey Hart
Civil Engineering
Petroleum Engineering
Jianhua Huang
Industrial Engineering
Electrical and Computer Engineering
Physics and Astronomy
Atmospheric Science
Computer Science
Economics
Agriculture Economics
Accounting
Geography
Valen Johnson
Sociology
Matthias Katzfuss
Atmospheric Sciences
Geography
Edward Jones
Bush School of Government
Veterinary Integrative Biosciences
Veterinary Medicine and Central Texas Specialty Hospital
Geography
Horticultural Studies
Sociology
Hispanic Studies
AgriLife College Station and AgriLife Stephenville
Educational Administration
Mikyoung Jun
Atmospheric Science
Geography
90
Hwa Chi Liang
Petroleum Engineering
James Long
Mathematics
Physics and Astronomy
Michael Longnecker
Nutrition and Food Science
Horticultural Sciences
Entomology
Ecosystem Science and Management
Landscape Architecture and Urban Planning
Nuclear Engineering
Biology
Small Animal Clinical Sciences
Bani Mallick
Mathematics
Petroleum Engineering
Industrial Engineering
Mechanical Engineering
Material Science
Nuclear Engineering
Marketing
Veterinary School
Aerospace Engineering
Mohsen Pourahmadi
Biostatistics and Epidemiology
Mathematics
Huiyan Sang
Health and Kinesiology
Architecture
Electrical and Computer Engineering
Industrial and Systems Engineering
Simon Sheather
Sociology
Landscape Architecture and Urban Planning
Information and Operations Management
Samiran Sinha
Health Science Center
Cliff Spiegelman
Entomology
Civil Engineering
91
Suojin Wang
Public Health
Architecture
Education and Human Development
Pharmacy
Lan Zhou
Animal Science
Biochemistry
Nutrition and Food Science
Entomology
92
SCH per FTE and Student/Faculty Ratio
Statistics Department Summary
SCH per Faculty FTE
STAT
FALL
2009
FALL
2010
FALL
2011
FALL
2012
FALL
2013
Student FTE to Faculty FTE Ratio (Excludes GATs FTE)
RANK
Faculty
LD
440.5
UD
401.9
UG
423.0
MS
205.8
PHD
54.6
TOTAL
175.1
GAT
Total
508.0
456.9
294.8
333.3
332.4
378.0
205.8
54.6
137.4
161.6
Faculty
533.5
462.9
500.1
219.7
46.6
196.8
GAT
Total
357.0
490.2
249.7
328.2
268.4
385.3
219.7
46.6
114.9
167.6
Faculty
783.9
366.1
509.6
302.7
45.4
202.5
GAT
Total
591.0
735.2
281.7
324.5
329.3
432.1
302.7
45.4
101.9
164.6
Faculty
799.5
396.4
540.2
119.5
233.9
GAT
Total
507.0
732.1
348.8
376.8
379.1
482.5
119.5
161.9
214.1
Faculty
713.5
633.4
664.6
110.6
275.6
GAT
Total
468.0
688.1
702.0
638.1
585.0
658.0
110.6
46.8
217.4
LD
UD
UG
MS
PHD
TOTAL
40.2
21.2
34.6
5.3
4.4
23.9
43.3
59.4
50.9
18.3
5.2
19.3
65.6
42.7
50.5
25.2
5.0
19.5
63.4
42.7
50.1
13.3
23.1
51.2
45.7
47.8
12.3
22.7
93
FACULTY SUMMARY
I. Personnel
a. Tenured and Tenure-Track
Faculty
Professor
Assistant Professor
Associate Professor
Distinguished Professor
b. Non-Tenure-Track Faculty
Senior Professor
Executive Professor
Visiting Professor
Visiting Assistant Professor
Visiting Associate Professor
Lecturer
Senior Lecturer
c. Postdoctoral Fellows
d. Graduate Majors
e. Undergraduate Majors
f. Support Staff
II. Instructional Activities
a. Graduate Semester Credit Hours
b. Undergraduate Semester Credit
Hours
c. PhD Degrees
d. Masters Degrees
e. Undergraduate Degrees
III. Research Activities
a. Research Publications
b. Research Presentations
c. Federal
d. State
e. Private/Non-Profit
f. Industrial/Corporate
g. International
h. Other Govt
Total
2009
2010
2011
2012
2013
34
33
33
33
33
19
9
4
2
8
0
0
1
0
0
2
5
16
170
0
15
18
6
7
2
6
0
0
1
0
0
1
4
17
170
0
18
18
5
7
3
9
0
0
3
1
0
1
4
7
184
0
18
20
3
7
3
13
1
1
2
1
0
2
6
10
162
0
16
19
5
6
3
13
1
1
3
1
0
2
5
13
162
0
16
5,814
14,300
5,962
14,571
5,688
14,599
5,342
15,800
5,331
16,992
6
19
0
6
16
0
11
23
0
10
36
0
8
34
0
90
143
3,724,360
0
195,926
0
3,468,746
95,198
7,484,230
99
129
3,726,479
0
185,024
0
1,749,042
42,445
5,702,990
80
143
4,049,321
135,434
173,888
0
1,749,042
28,142
6,135,826
92
99
3,562,405
67,441
128,339
0
1,749,042
719
5,507,945
72
94
3,173,948
39,807
558,599
0
492,881
1,407
4,266,642
94
95
Goldplate Funding 2007-2015
FY2007
FY2008
FY2009
FY2010
FY2011
FY2012
FY2013
FY2014
FY2015
$3,668,881
$3,785,045
$3,994,639
$4,097,517
$4,022,608
$3,886,025
$3,903,245
$4,035,427
$4,120,724
$82,741
$82,741
$82,741
$82,741
$82,741
$41,741
$41,741
$41,741
$41,741
Staff
$278,078
$290,591
$299,263
$304,237
$304,237
$235,677
$235,677
$249,975
$258,913
GAT/GANT
$345,198
$345,198
$345,198
$345,198
$345,198
$142,270
$142,270
$142,270
$142,270
$45,608
$117,508
$117,508
$117,508
$117,508
$103,830
$103,830
$103,139
$103,139
$4,420,506
$4,621,083
$4,839,349
$4,947,201
$4,872,292
$4,409,543
$4,426,763
$4,572,552
$4,666,787
Budget
Reduction
#1
Budget
Reduction
#2
Faculty Salaries
Summer Teaching
Operating
TOTAL
96
Semester Credit Hours Taught by Faculty Rank for Fall 2009
Undergraduate
Rank
Professor
% of Level
% of Rank
Assoc.
Professor
% of Level
% of Rank
Asst. Professor
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Senior Lecturer
% of Level
% of Rank
Lecturer
% of Level
% of Rank
Visiting
% of Level
% of Rank
Subtotal
% of Level
% of Rank
GATs - Lecture
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Total
Graduate
1XX
2XX
3XX
4XX
Total
MS
PhD
Total
0
0.0
0.0
474
16.7
20.7
285
8.1
12.4
60
44.4
2.6
819
12.7
35.7
902
49.0
39.4
571
61.1
24.9
1,473
53.0
64.3
Grand
Total
2,292
24.8
100.0
0
438
0
0
438
465
168
633
1,071
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
15.4
40.9
441
15.6
42.5
1,353
47.7
30.7
162
5.7
11.5
558
19.7
100.0
0
0.0
0.0
720
25.4
35.6
762
26.9
27.0
762
26.9
27.0
2,835
0.0
0.0
332
9.5
32.0
617
17.6
14.0
823
23.5
58.7
0
0.0
0.0
0
0.0
0.0
823
23.5
40.7
2,064
58.9
73.0
2,064
58.9
73.0
3,504
0.0
0.0
0
0.0
0.0
60
44.4
1.4
75
55.6
5.3
0
0.0
0.0
0
0.0
0.0
75
55.6
3.7
0
0.0
0.0
0
0.0
0.0
135
6.8
40.9
773
11.9
74.5
2,030
31.4
46.1
1,060
16.4
75.6
558
8.6
100.0
0
0.0
0.0
1,618
25.0
79.9
2,826
43.6
100.0
2,826
43.6
100.0
6,474
25.2
43.4
177
9.6
17.0
1,544
83.8
35.1
250
13.6
17.8
0
0.0
0.0
48
2.6
76.2
298
16.2
14.7
0
0.0
0.0
0
0.0
0.0
1,842
18.0
15.7
88
9.4
8.5
827
88.4
18.8
93
9.9
6.6
0
0.0
0.0
15
1.6
23.8
108
11.6
5.3
0
0.0
0.0
0
0.0
0.0
935
22.8
59.1
265
9.5
25.5
2,371
85.4
53.9
343
12.4
24.4
0
0.0
0.0
63
2.3
100.0
406
14.6
20.1
0
0.0
0.0
0
0.0
0.0
2,777
11.6
100.0
1,038
11.2
100.0
4,401
47.6
100.0
1,403
15.2
100.0
558
6.0
100.0
63
0.7
100.0
2,024
21.9
100.0
2,826
30.5
100.0
2,826
30.5
100.0
9,251
97
Semester Credit Hours Taught by Faculty Rank for Fall 2010
Undergraduate
Rank
Professor
% of Level
% of Rank
Assoc.
Professor
% of Level
% of Rank
Asst. Professor
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Senior Lecturer
% of Level
% of Rank
Lecturer
% of Level
% of Rank
Visiting
% of Level
% of Rank
Subtotal
% of Level
% of Rank
GATs - Lecture
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Total
1XX
Graduate
2XX
3XX
4XX
Total
0
0.0
0.0
0
360
12.0
15.5
660
376
10.6
16.2
398
135
100.0
5.8
0
871
13.0
37.6
1,058
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
22.0
38.0
618
20.6
52.6
1,638
54.6
31.3
231
7.7
18.3
596
19.9
100.0
0
0.0
0.0
827
27.6
43.6
536
17.9
23.2
536
17.9
23.2
3,000
11.2
22.9
285
8.0
24.2
1,059
29.8
20.2
726
20.4
57.6
0
0.0
0.0
0
0.0
0.0
726
20.4
38.3
1,775
49.8
76.8
1,775
49.8
76.8
3,561
0.0
0.0
0
0.0
0.0
135
100.0
2.6
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
135
15.8
60.9
903
13.5
76.8
2,832
42.3
54.1
957
14.3
76.0
596
8.9
100.0
0
0.0
0.0
1,553
23.2
81.9
2,311
34.5
100.0
2,311
34.5
100.0
6,696
PhD
Total
929
48.4
40.1
503
519
62.8
22.4
177
1,448
52.8
62.4
680
Grand
Total
2,319
24.6
100.0
1,738
26.2
28.9
207
10.8
17.6
1,639
85.5
31.3
243
12.7
19.3
0
0.0
0.0
36
1.9
88.9
279
14.5
14.7
0
0.0
0.0
0
0.0
0.0
1,918
21.4
10.2
66
8.0
5.6
762
92.2
14.6
60
7.3
4.8
0
0.0
0.0
5
0.5
11.1
65
7.8
3.4
0
0.0
0.0
0
0.0
0.0
826
24.8
39.1
273
9.9
23.2
2,401
87.5
45.9
303
11.0
24.0
0
0.0
0.0
41
1.5
100.0
344
12.5
18.1
0
0.0
0.0
0
0.0
0.0
2,744
18.4
100.0
1,176
12.5
100.0
5,233
55.4
100.0
1,260
13.4
100.0
596
6.3
100.0
41
0.4
100.0
1,896
20.1
100.0
2,311
24.5
100.0
2,311
24.5
100.0
9,440
MS
98
Semester Credit Hours Taught by Faculty Rank for Fall 2011
Undergraduate
Graduate
Professor
% of Level
% of Rank
0
0.0
0.0
426
14.6
16.8
498
14.5
19.7
177
100.0
7.0
1,101
16.9
43.5
945
51.2
37.4
483
58.5
19.1
1,428
53.4
56.5
Grand
Total
2,529
27.5
100.0
Assoc.
Professor
% of Level
% of Rank
Asst. Professor
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Senior Lecturer
% of Level
% of Rank
Lecturer
% of Level
% of Rank
Visiting
% of Level
% of Rank
Other
% of Level
% of Rank
Subtotal
% of Level
% of Rank
GATs - Lecture
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Total
0
0
413
0
413
353
139
492
905
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
585
20.1
59.7
1,011
34.7
22.9
234
8.0
20.2
1,077
37.0
100.0
0
0.0
0.0
0
0.0
0.0
1,311
45.0
49.7
591
20.3
27.6
591
20.3
27.6
2,913
12.0
45.6
344
10.0
35.2
1,256
36.6
28.4
627
18.3
54.1
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
627
18.3
23.8
1,550
45.1
72.4
1,550
45.1
72.4
3,432
0.0
0.0
0
0.0
0.0
177
100.0
4.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
177
6.3
45.6
929
14.3
94.9
2,444
37.5
55.4
861
13.2
74.4
1,077
16.5
100.0
0
0.0
0.0
0
0.0
0.0
1,938
29.7
73.4
2,141
32.8
100.0
2,141
32.8
100.0
6,522
19.1
39.0
9
0.5
0.9
1,307
70.8
29.6
198
10.7
17.1
0
0.0
0.0
309
16.7
94.5
33
1.8
42.3
540
29.2
20.5
0
0.0
0.0
0
0.0
0.0
1,847
16.8
15.4
41
5.0
4.2
663
80.4
15.0
99
12.0
8.5
0
0.0
0.0
18
2.2
5.5
45
5.5
57.7
162
19.6
6.1
0
0.0
0.0
0
0.0
0.0
825
18.4
54.4
50
1.9
5.1
1,970
73.7
44.6
297
11.1
25.6
0
0.0
0.0
327
12.2
100.0
78
2.9
100.0
702
26.3
26.6
0
0.0
0.0
0
0.0
0.0
2,672
9.8
100.0
979
10.7
100.0
4,414
48.0
100.0
1,158
12.6
100.0
1,077
11.7
100.0
327
3.6
100.0
78
0.8
100.0
2,640
28.7
100.0
2,141
23.3
100.0
2,141
23.3
100.0
9,194
Rank
1XX
2XX
3XX
4XX
Total
MS
PhD
Total
99
Semester Credit Hours Taught by Faculty Rank for Fall 2012
Undergraduate
Rank
Professor
% of Level
% of Rank
Assoc.
Professor
% of Level
% of Rank
Asst. Professor
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Senior Lecturer
% of Level
% of Rank
Lecturer
% of Level
% of Rank
Visiting
% of Level
% of Rank
Other
% of Level
% of Rank
Subtotal
% of Level
% of Rank
GATs - Lecture
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Total
1XX
Graduate
2XX
3XX
4XX
Total
0
0.0
0.0
0
114
3.6
5.0
717
597
16.3
26.0
233
194
100.0
8.4
0
905
12.9
39.3
950
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
22.6
46.5
357
11.2
100.0
1,188
37.4
28.3
234
7.4
12.3
1,248
39.3
100.0
0
0.0
0.0
0
0.0
0.0
1,482
46.6
44.1
507
16.0
25.6
507
16.0
25.6
3,177
6.4
15.1
0
0.0
0.0
830
22.7
19.8
1,361
37.2
71.3
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
1,361
37.2
40.5
1,472
40.2
74.4
1,472
40.2
74.4
3,663
0.0
0.0
0
0.0
0.0
194
100.0
4.6
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
194
13.5
61.6
357
5.1
100.0
2,212
31.4
52.7
1,595
22.7
83.5
1,248
17.7
100.0
0
0.0
0.0
0
0.0
0.0
2,843
40.4
84.5
1,979
28.1
100.0
1,979
28.1
100.0
7,034
PhD
Total
926
53.1
40.3
400
469
61.5
20.4
193
1,395
55.6
60.7
593
Grand
Total
2,300
24.1
100.0
1,543
22.9
25.9
0
0.0
0.0
1,326
76.0
31.6
246
14.1
12.9
0
0.0
0.0
159
9.1
84.1
14
0.8
87.5
419
24.0
12.5
0
0.0
0.0
0
0.0
0.0
1,745
25.3
12.5
0
0.0
0.0
662
86.8
15.8
69
9.0
3.6
0
0.0
0.0
30
3.9
15.9
2
0.3
12.5
101
13.2
3.0
0
0.0
0.0
0
0.0
0.0
763
23.6
38.4
0
0.0
0.0
1,988
79.3
47.3
315
12.6
16.5
0
0.0
0.0
189
7.5
100.0
16
0.6
100.0
520
20.7
15.5
0
0.0
0.0
0
0.0
0.0
2,508
16.2
100.0
357
3.7
100.0
4,200
44.0
100.0
1,910
20.0
100.0
1,248
13.1
100.0
189
2.0
100.0
16
0.2
100.0
3,363
35.2
100.0
1,979
20.7
100.0
1,979
20.7
100.0
9,542
MS
100
Semester Credit Hours Taught by Faculty Rank for Fall 2013
Undergraduate
Rank
Professor
% of Level
% of Rank
Assoc.
Professor
% of Level
% of Rank
Asst. Professor
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Senior Lecturer
% of Level
% of Rank
Lecturer
% of Level
% of Rank
Visiting
% of Level
% of Rank
Other
% of Level
% of Rank
Subtotal
% of Level
% of Rank
GATs - Lecture
% of Level
% of Rank
Subtotal
% of Level
% of Rank
Total
1XX
Graduate
2XX
3XX
4XX
Total
0
0.0
0.0
0
780
23.5
27.6
339
0
0.0
0.0
300
213
100.0
7.5
0
993
12.5
35.1
639
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
10.2
34.1
468
14.1
32.0
1,587
47.8
30.0
0
0.0
0.0
1,158
34.9
100.0
342
10.3
30.8
0
0.0
0.0
1,500
45.2
31.2
234
7.0
40.0
234
7.0
40.0
3,321
6.8
30.2
966
21.8
66.0
1,266
28.5
24.0
2,235
50.4
88.7
0
0.0
0.0
585
13.2
52.7
0
0.0
0.0
2,820
63.6
58.6
351
7.9
60.0
351
7.9
60.0
4,437
0.0
0.0
0
0.0
0.0
213
100.0
4.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
0
0.0
0.0
213
8.0
64.2
1,434
18.0
98.0
3,066
38.5
58.0
2,235
28.0
88.7
1,158
14.5
100.0
927
11.6
83.5
0
0.0
0.0
4,320
54.2
89.8
585
7.3
100.0
585
7.3
100.0
7,971
PhD
Total
1,263
65.9
44.7
256
571
71.8
20.2
100
1,834
67.6
64.9
356
Grand
Total
2,827
26.5
100.0
995
13.4
25.7
9
0.5
0.6
1,528
79.7
28.9
201
10.5
8.0
0
0.0
0.0
168
8.8
15.1
20
1.0
83.3
389
20.3
8.1
0
0.0
0.0
0
0.0
0.0
1,917
12.6
10.1
21
2.6
1.4
692
87.0
13.1
84
10.6
3.3
0
0.0
0.0
15
1.9
1.4
4
0.5
16.7
103
13.0
2.1
0
0.0
0.0
0
0.0
0.0
795
13.1
35.8
30
1.1
2.0
2,220
81.9
42.0
285
10.5
11.3
0
0.0
0.0
183
6.7
16.5
24
0.9
100.0
492
18.1
10.2
0
0.0
0.0
0
0.0
0.0
2,712
9.3
100.0
1,464
13.7
100.0
5,286
49.5
100.0
2,520
23.6
100.0
1,158
10.8
100.0
1,110
10.4
100.0
24
0.2
100.0
4,812
45.0
100.0
585
5.5
100.0
585
5.5
100.0
10,683
MS
101
History of Courses Taught: Statistics Department
STAT
201
STAT
211
STAT
212
STAT
301
STAT
302
STAT
303
STAT
307
STAT
407
STAT
414
STAT
485
STAT
601
STAT
604
STAT
607
STAT
610
STAT
612
STAT
613
STAT
614
STAT
615
STAT
618
STAT
620
Fall 2007
Sections Enrollment
3
173
Fall 2008
Sections Enrollment
4
240
Fall 2009
Sections Enrollment
3
254
Fall 2010
Sections Enrollment
3
256
Fall 2011
Sections Enrollment
2
209
Fall 2012
Sections Enrollment
3
246
Total
Sections
18
Total
Enrollment
1,378
Average
Enrollment
77
12
546
10
591
10
592
9
622
6
634
6
697
53
3,682
69
Prin of Stat II
1
58
1
77
2
99
2
122
2
128
2
116
10
600
60
Intro to
Biometry
Statistical
Methods
Statistical
Methods
Sample
Survey Tcnq
Principles
Sample Surv
Math
Statistics I
Directed
Studies
Statistical
Analysis
Stat Comp
Anly Prob
Statistical
Computations
Sampling
2
85
2
75
2
87
2
74
2
77
2
95
12
493
41
13
611
13
598
13
610
13
615
12
589
13
634
77
3,657
47
10
488
12
462
10
444
10
479
10
478
10
492
62
2,843
46
1
26
1
20
1
27
1
19
4
92
23
1
9
1
12
1
17
1
10
1
22
1
23
6
93
16
1
30
1
39
1
20
1
35
1
37
1
41
6
202
34
1
2
1
2
2
13
283
22
7
134
19
Elem Stat
Inference
Prin of Stat I
Distribution
Theory
Thry of
Statistics I
Thry of Linear
Models
Intermed Thry
of Stat
Adv Thry of
Statistics
Probability for
Stat
Stochastic
Processes
Stat Mach
Learn &
Mining
Stat Large
Sample Thry
3
54
2
37
2
41
2
44
1
28
2
30
2
35
2
41
2
11
2
9
2
16
2
9
2
83
2
72
2
98
3
93
1
30
1
12
1
28
1
16
1
24
1
1
1
15
1
6
10
22
1
1
21
12
1
1
2
48
2
59
2
63
2
63
4
126
32
2
10
3
24
13
79
6
2
90
2
94
4
184
46
9
346
38
6
115
19
1
24
24
3
40
13
1
14
1
15
13
8
1
14
1
13
2
27
14
1
6
1
15
5
51
10
1
21
1
21
21
2
37
18
102
STAT
623
STAT
630
STAT
632
STAT
636
STAT
641
STAT
643
STAT
645
STAT
647
STAT
648
STAT
651
STAT
652
STAT
653
STAT
657
STAT
658
STAT
661
STAT
671
STAT
673
STAT
681
STAT
684
STAT
685
STAT
689
STAT
691
Total
Stat Meth for
Chem
Overview of
Math Stat
Stat Decision
Thry
Stat Meth II
Bayes Model
Meth
Multivariate
Anly
Methods of
Stat I
Biostatistics I
Appl Biostat &
Data Anly
Spatial
Statistics
Applied Stat &
Data Analys
Stat in
Research I
Stat in
Research II
Stat in
Research III
Advanced
Programming
Sas
Transportation
Statistic
Statistical
Genetics
Stat Data
Modeling I
Time Series
Anly I
Seminar
Professional
Internshp
Directed
Studies
Special
Topics in
Research
1
6
2
56
2
40
3
53
3
58
1
19
1
26
1
10
1
27
3
57
2
49
1
6
6
15
313
21
4
82
20
1
13
1
14
2
27
14
2
18
2
45
2
27
2
27
2
26
2
41
12
184
15
2
55
2
29
2
49
2
25
2
31
2
29
12
218
18
1
18
2
10
1
6
1
5
1
4
6
43
7
2
8
3
17
5
25
5
1
8
1
6
1
8
1
19
1
15
1
8
6
64
11
1
17
1
11
1
11
3
39
13
5
235
5
291
6
208
5
185
5
207
4
170
30
1,296
43
4
86
3
91
3
89
4
92
3
53
3
74
20
485
24
2
17
2
17
8
2
26
2
1
1
3
1
3
1
14
24
3
2
27
2
46
8
123
15
1
11
1
11
2
22
11
1
7
2
10
5
2
6
3
1
16
1
9
3
39
13
2
30
2
31
3
37
2
38
2
38
2
40
13
214
16
2
18
2
16
3
22
4
25
3
14
3
14
17
109
6
11
15
12
16
7
13
9
14
7
17
5
13
51
88
2
2
20
2
20
5
39
2
13
1
4
2
10
14
106
8
12
21
19
41
22
47
20
54
20
49
19
40
112
252
2
105
2,890
117
3,019
116
3,036
117
3,122
105
3,044
101
3,166
661
18,277
985
103
IV.
APPENDIX
104
APPENDIX A.
MS Statistics and Online Programs
In Fall 2007, under the direction of Mike Speed, Director and Simon Sheather, Department
Head, the department’s first cohort of 20 students were enrolled in the Distance Learning MS in
Applied Statistics program. In 2008, the Transcripted Certificate of Applied Statistics was introduced.
In 2009, a joint Texas A&M University/SAS certificate was approved with currently 116 students
having received a certificate. This same year, we celebrated our first graduate of the program and the
number of supported on-campus graduate students was expanded with the introduction of
Technology Teaching Assistants. In the last academic year there were over 1000 enrollments in
graduate level Statistics courses online with 117 professionals having completed their MS degree in
Statistics. In terms of student quality, more than 90% of distance learning students to date have passed
the Masters Qualifying Exam at their first attempt. Our alumni have proven successful by moving on
to excel in their fields as vice presidents, teachers, engineers, analysts and scientists working for fortune
500 companies such as, Intel Corp, Chevron, Bank of America and Amgen.
Below is a selection of the employers of our graduates.
Addx Corporation
Advanced Analytics at Cardinal Health
Amgen
Armstrong World Industries
AT&T
Audimation Services, Inc.
Bank of America
BBA Solutions
Biomedical Research Foundation
Boeing Commercial Airplanes
CA Technologies
Capital One Financial Corp., Plano
Chevron
Chief Business Office - Veterans Health
Collin College
Computer Sciences Corporation
Continuum Analysis
Corning Incorporated
CRO
Cyberonics
Deloitte
Denton High School
eBay Enterprise
Ericsson
Gallagher Benefit Services
Highmark Health
Humble ISD
IMS Health
INC Research
Infinity Property & Casualty Company
Informatics Centre of Excellence, Cancer Care
Ontario
Intel Corporation
Investment Solutions Group
Janus Capital
KLAS Enterprises
Korn Ferry
Laboratory Corporation of America
Lake Region Medical
Leidos Biomedical Research, Inc for NCI
105
Mathnasium RVA
Medtronic
Montgomery High School
National Oilwell Varco (NOV)
Newmont Mining Corporation
North Shore Long Island Jewish Health System
Pearson North America
PPD
PRA International
Pros
QBE First
Rigid Closed Top Division
Royal Bank of Canada
RTI International
Sandia National Laboratories
SAS
Slalom Consulting
SpectraCell Laboratories, Inc
St. Jude Medical
SUNY Adirondack College
SUNY Upstate Clinical Campus
Systems Kinetics
The EMMES Corporation
TheHunt.com
Transamerica
U. S. Air Force
U. S. Department of State
U. S. Gypsum Co.
University of Houston
University of Kansas Medical Center
University of Washington
University of Washington - Dept of Surgery
UPC Cablecom
Utah Insurance Group
Vanderbilt University Medical Center
Washington University, St. Louis
Zurich North America
106
In 2011, Mike Speed retired as Director and Simon Sheather took on this role, as well as
continued his role as Department Head. From 2006-2013, more than 10 new graduate courses were
introduced. The following is a complete list of courses that have been offered at a distance, including
the new courses that were designed specifically for distance delivery.
The courses marked * are new courses.
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
STAT 601 Statistical Analysis
STAT 604 Topics in Statistical Computations
STAT 607 Sampling
STAT 608 Regression Analysis
STAT 626 Methods in Time Series Analysis
STAT 630 Overview of Mathematical Statistics
STAT 636 Methods in Multivariate Analysis
STAT 638 Introductions to Applied Bayesian Methods*
STAT 641 The Methods of Statistics I
STAT 642 The Methods of Statistics II
STAT 643 Biostatistics I
STAT 645 Applied Biostatistics and Data Analysis*
STAT 646 Statistical Bioinformatics*
STAT 651 Statistics in Research I
STAT 652 Statistics in Research II
STAT 653 Statistics in Research III
STAT 656 Applied Analytics Using SAS Enterprise Miner*
STAT 657 Advanced Programming Using SAS*
STAT 659 Categorical Data Analysis
STAT 681 Seminar
STAT 684 Consulting Credit
STAT 685 Directed Studies
Since the program’s inception and in light of the rapid growth, the need for more faculty and
staff was imperative to continue the program’s success. In fall 2007, the program operated with a
director, one part-time program coordinator, an IT specialist and six faculty to teach our online
students. In 2008/2009, with applications increasing, and our enrollment more than quadrupling the
first year, the need to hire a full time program coordinator, business coordinator to handle accounting
and a software specialist to assist the IT specialist was eminent. At this time, the number of courses
being taught had increased to thirteen and the number of faculty teaching were ten.
To date, with the continued increase in numbers and ultimate success of the Distance
107
Learning MS in Applied Statistics program, certificate and non-degree seeking students, there are
more than 500 students enrolled taking more than 1000 graduate level statistics courses. Currently,
this entire program is run with an academic director, program manager, administrative assistant, a
chief of operations and software specialist who oversee technology and 16 TTAs who aid in the set
up and recording of classes. In addition, there is a business coordinator who splits her time with other
programs. There are currently ten faculty teaching seventeen courses.
The table below summarizes the course enrollments in distance education each semester since
the Fall 2008 semester.
Semester
Fall 2008
Fall 2009
Fall 2010
Fall 2011
Fall 2012
Fall 2013
Fall 2014
In State
105
123
186
167
173
176
271
Out of State
87
157
224
269
274
233
300
Total
192
280
410
436
447
409
571
Spring 2009
Spring 2010
Spring 2011
Spring 2012
Spring 2013
Spring 2014
Spring 2015
100
129
137
147
171
211
253
106
152
221
269
260
254
292
206
281
358
416
431
465
545
Summer 2009
Summer 2010
Summer 2011
Summer 2012
Summer 2013
Summer 2014
Summer 2015
87
66
84
132
140
179
200*
92
101
145
156
143
141
146*
179
167
229
288
283
320
346*
*Projected numbers
108
The table below summarizes graduates by calendar year.
2009
2010
2011
2012
2013
2014
2015
2
11
13
26
27
38
46*
*Projected numbers
The table below summarizes the number of certificates completed by calendar year.
2008
2009
2010
2011
2012
2013
2014
2
8
7
22
35
19
19
109
110
APPENDIX B.
MS ANALYTICS OVERVIEW
THE NEED FOR ANALYTICS
The U.S. is suffering through a shortage of people with deep analytical skills to analyze big
data, an issue deeply impacting corporations. By 2018, that gap is expected to reach between 140,000
and 190,000, according to the McKinsey Global Institute.
In order to regain a competitive advantage, businesses need to retrain the talent currently in
place.
THE HISTORY OF THE PROGRAM
Approvals Needed to Offer the MS Analytics Degree
111
The Department of Statistics has teamed with the Mays Business School to offer a Master of Science
in Analytics, ideal for corporate managers and professionals. The degree is geared towards those with
expertise in a wide array of industries: oil & gas, retail, healthcare, electronics, and energy.
The program will culminate in a quantitative analysis project specific to your employer. The part-time,
five-semester program will provide graduates with comprehensive and balanced training in statistical
and business processes. We’re looking to produce data scientists who are thought leaders and
innovators
THE MODERN SKILL-SET
• Business Acumen to ask the RIGHT business question.
• Deep Analytical Skills such as market analysis, predictive modeling, web analytics, risk analysis,
forecasting
• Technical Expertise such as programming, data warehousing, mining, and visualization
• Soft Skills such as teamwork, communication, and presentation skills
CURRICULUM
• 75% Statistics and 25% Business.
112
LOCATION
CITYCENTRE, HOUSTON
Our program is taught Tuesday and Thursday evenings in-person at Houston's CITYCENTRE (I-10
& Beltway 8). The CityCentre facility was designed by a team of faculty, staff and students to be the
ideal environment for executive learning.
We also offer the degree at a distance via live video stream for individuals outside of a 50-mile radius
of Houston throughout North America (USA, Mexico, Canada). Live video participants will interact
with students and faculty in Houston and are required to appear in-person twice: a 3-day orientation
in Week 0 and in their final semester to present their capstone project. Our goal is to replicate the
classroom experience, even if you are not in Houston. In addition to giving students the ability to
join live classes via video, we record each class. The flexible delivery ensures you won’t miss any
material in the event you are unable to make it to class or have to travel for work.
ADMISSION
Admission to the Texas A&M Masters in Analytics program is highly competitive.
Strong candidates must meet the following criteria and qualifications:
• Grades
o Competitive undergraduate or graduate GPA or strong GRE/GMAT scores
• Statistics Competency
o Completed at least one statistics course with an A or B
• Work Experience
o At minimum 3 years of full-time work experience
• Purpose
o A well-written statement of purpose about how this analytics degree will help your
organization
• Organizational Support
o Support from current employer for access and mentorship with a business problem
and large data set
REQUIRED APPLICATION MATERIALS
• Completed pre-questionnaire
(http://analytics.stat.tamu.edu/#contact)
• 3 letters of recommendation or 3 recommendation forms
(http://www.stat.tamu.edu/dist/Graduate_Letter_of_Rec.pdf)
• Unofficial GRE/GMAT scores if available (may be waived after transcript review)
• Unofficial college transcripts
• Current résumé
Once your complete information is reviewed by a committee, you will receive additional instructions
regarding the official application process, should you progress to this stage.
Prior to final admission, all candidates will be required to interview.
113
COST
The total cost of a Masters in Analytics degree is $50,000 ($10,000 per semester), which includes
tuition, required fees, books, supplies, hotel and meals during orientation, and a laptop preloaded with
all necessary software. No assistantships or scholarships are available at this time. Given the value
added to your organization through the unique work-based project, we strongly suggest that enrollees
request sponsorship from their employer for the degree.
COMPETITION
In just 2 years has grown from a handful to over 90 data science and analytics programs.
114
APPENDIX C.
Proposal for an Undergraduate Major in Statistics.
In the summer of 2014, the Department voted to develop an undergraduate degree program in
Statistics. The overall curriculum was designed during the fall semester. Various faculty members
developed nine new undergraduate courses to be included in the curriculum. Notable aspects of the
curriculum are nine required courses and two elective courses in statistics, four required and two elective
courses in mathematics, two elective computer science courses, and four elective courses in an outside
specialization area. First-year students will take an overview course that introduces the students to the
field of statistics. The curriculum is designed to be flexible, allowing a student, in conjunction with the
undergraduate advisor, to develop a program that meets the student’s needs. For example, a student
planning to go to graduate school in statistics could take four additional mathematics courses as the
outside specialization area. A student who wished to work in genomics would take biologically oriented
mathematics and statistics electives and would have biology/genetics as the outside specialization area.
All students will be required to take a writing-intensive capstone course.
The program was approved by the College of Science Undergraduate Curriculum Committee
in March 2015. The TAMU Undergraduate Curriculum Committee will consider the program during
their April 2015 meeting. We anticipate that students will be able to enroll in the program in Fall 2016
with an annual enrollment of more than 60 new students per year. A document describing the program
and its motivation follows. Pending approval at the University level, this document will be forwarded
to the Texas Higher Education Coordinating Board for final approval of the undergraduate major.
115
Texas A&M University
Bachelor of Science with a major in Statistics
Program Review Outline
BACKGROUND & PROGRAM DESCRIPTION
Administrative Unit: Department of Statistics, College of Science
The educational objectives of the new program are: master the depth of knowledge required for the
degree; work effectively with data; demonstrate critical thinking; communicate effectively; practice
personal and social responsibility; demonstrate social, cultural, and global competence; prepare to
engage in lifelong learning; work collaboratively. Evaluation will be done via performance metrics on
required coursework, in addition to data we will collect on the students after they have completed the
program. For more details, see the main proposal document.
The program curriculum will include existing courses in the Departments of Statistics,
Mathematics, Computer Science and Engineering, and Industrial and Systems Engineering. In
addition, the Department of Statistics will develop ten new courses for the program.
The proposed implementation date is Fall 2016.
Texas A&M University certifies that the proposed new degree program meets the criteria under the
19 Texas Administrative Code, Section 5.45 in regards to need, quality, financial and faculty
resources, standards and costs. New costs during the first five years will not exceed $2 million.
I. NEED
A. Employment Opportunities
Statisticians are in demand in all sectors of society. Statisticians use statistical methods to
collect and analyze data and help solve real-world problems in business, engineering, the
sciences, and other fields. Nearly every agency in the federal government employs
statisticians.
Biostatisticians work in pharmaceutical companies, public health agencies, and hospitals. In
business, statisticians design experiments for product testing and development. Actuaries use
mathematics, statistics, and financial theory to study uncertain future events, especially those
of concern to insurance and pension companies.
In a 2009 NY Times article, statistics was cited as being a rapidly expanding field, with
employers such as Google and IBM hiring increasing numbers from the field. “I keep saying
that the sexy job in the next 10 years will be statisticians. And I’m not kidding.” 2 Hal Varian,
2
Lohr, Steve. “For Today’s Graduate, Just One Word: Statistics.” New York Times. 5 August 2009.
116
chief economist at Google. “Data availability is going to continue to grow. To make that
data useful is a challenge. It’s generally going to require human beings to do it,” according
to Dr. Varian.
According to the Bureau of Labor Statistics, there were 24,950 workers classified as
statisticians in 2013. This represents a 21% increase in the five years since 2008. The field
was projected to grow by a further 27% (classified by BLS as “much faster than average”)
during 2012 – 2022. 3
The Texas Workforce Commission currently lists 500 jobs with the keyword of “statistics”
(searched July 11, 2014). According to The Wall Street Journal’s Numbers Guy, Carl Bialik, as
of March 2013, there were 28,305 postings for jobs in statistics, analytics, and “big data” at
the jobs website icrunchdata; this was up from 16,500 three years earlier. 4
McKinsey Global Institute published a study in May 2011 entitled “Big Data: The next
frontier for innovation, competition, and productivity” that predicts “by 2018 the US will
have a shortage of 140,000 – 190,000 people with deep analytical skills as well as 1.5 million
managers and analysts with know-how to use the analysis of big data to make effective
decisions.” 5
In December 2014, LinkedIn published a list of the year’s “hottest skills” for recruiting on
the site. Statistical analysis and data mining was listed as number one. 6
B. Projected Enrollment
We anticipate enrollments of 25, 45, 55, 60, and 65 students in the first five years, respectively.
At steady state, we expect annual enrollments of 65 students, for an approximate total of
260 students in the program.
C. Existing State Programs
Rice University, Baylor University, the University of Texas at San Antonio, Southern
Methodist University, and the University of Houston-Downtown all offer B.S. degrees in
statistics.
However, the Department of Statistics at Texas A&M would be the only large statistics
department in Texas to offer a B.S. degree in statistics. The Department of Mathematics
already offers an Applied Mathematical Sciences (APMS) degree that offers specialization in,
among other things, statistics. However, there are very few students in the statistics track (5
or fewer a year), so we expect the vast majority of students pursuing a statistics degree to be
new students.
3
4
5
6
http://www.bls.gov/oes/2013/may/oes152041.htm
http://www.bls.gov/ooh/math/statisticians.htm
http://online.wsj.com/articles/SB10001424127887323478304578332850293360468
http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation
http://talent.linkedin.com/blog/index.php/2014/12/the-25-hottest-skills-to-recruit-for-on-linkedin
117
II. QUALITY & RESOURCES
A. Faculty
The Department of Statistics has an adequate number of faculty for teaching the program’s
courses in the first two years, since many elective courses will not be needed in the first two
years of the program. Rather, during the first two years of the program, students in the new
program will take courses that are currently offered as service courses. We have requested
new faculty positions, to begin in the third year, and these new faculty will be responsible
for teaching the remaining elective courses.
Courses will be assigned to faculty by matching course content to faculty interests and areas
of expertise. The duties of current faculty that are reassigned will be met by reducing their
teaching duties in the graduate program. We anticipate that this reassignment can be
managed to have a minimal effect on the graduate programs of the department. The
required courses outside the Department of Statistics are existing courses on the TAMU
College Station campus.
B. Program Administration
Academic advising will be provided by the Director of Undergraduate Programs as well as by a
new full-time staff member dedicated to academic advising. An existing staff member will have
one quarter of their time reassigned to assist with administrative tasks for the program.
C. Other Personnel
None.
D. Supplies, Materials
No special supplies or materials will be necessary.
E. Library
No additional library resources will be necessary.
F. Equipment, Facilities
The program will use existing facilities of the Department of Statistics and the College of
Science for classroom, office space, and computer labs. Facilities and equipment will be made
available and adequate to conduct this program and to ensure quality in teaching and learning,
and be consistent with standards of similar programs in Texas and the US.
G. Accreditation
Texas A&M is current with institutional accreditation by the Southern Association of Colleges
and Schools. There are no specialized accreditation agencies currently available for
undergraduate statistics.
118
Catalog Description
Statistics is the science of collecting and analyzing data for the purpose of making confident
decisions in the presence of uncertainty. Large and complex data sets are ubiquitous in the modern
day and age, and statisticians are in high demand. Multidisciplinary application areas vary widely and
include health and medicine, business, physical sciences, engineering, environmental studies, and
government. The curriculum in statistics provides training in all necessary areas, including a
mathematical and probabilistic foundation, strategies for designing studies and collecting data, the
visualization and analysis of data using popular software such as SAS and R, and the process of
using sample data to draw confident conclusions about a population. Depending on the electives
selected, a student completing this program will be prepared to enter employment as a statistical
analyst or continue to graduate school in statistics or a related field.
119
Curriculum in Statistics
FRESHMAN YEAR
First Semester
ENGL 104 Composition
and Rhetoric
HIST 105 History of the
U.S.
MATH 171 Analytic
Geometry and Calculus
Science Elective1
(Th-Pr)
(3-0)
Cr
3
Second Semester
HIST 106 History of the U.S.
(Th-Pr)
(3-0)
Cr
3
(3-0)
3
MATH 172 Calculus
(4-0)
4
(4-0)
4
STAT 182 Foundations of
Statistics
(1-0)
1
4
Computer science elective2
Science Elective1
4
4
16
14
SOPHOMORE YEAR
First Semester
Communication
requirement3
(Th-Pr)
(3-0)
Cr
3
Second Semester
MATH 304 Linear Algebra
(Th-Pr)
(3-0)
Cr
3
MATH 221 Several
Variables Calculus
POLS 206 American Natl.
Government
STAT 211 Principles of
Statistics I
(4-0)
4
POLS 207 State and Local
Government
(3-0)
3
(3-0)
3
STAT 212 Principles of Statistics II
(3-0)
3
(3-0)
3
Computer science elective2
4
3
16
Elective hours4
3
16
Science Elective1
JUNIOR YEAR
First Semester
STAT 404 Statistical
Computing
STAT 414 Mathematical
Statistics I
Mathematics elective5
Outside specialization
elective6
Elective hours4
(Th(3-0)
Cr
3
Second Semester
STAT 408 Linear Models
(Th-Pr) Cr
(3-0)
3
(3-0)
3
STAT 415 Mathematical
Statistics II
Outside specialization elective6
Elective hours4
(3-0)
3
3
3
15
3
3
6
15
120
SENIOR YEAR
First Semester
STAT 406 Design and
Analysis of Experiments
Mathematics elective5
Statistics elective7
Outside specialization
elective6
Elective hours4
(Th-Pr)
(3-0)
Cr
3
3
3
3
3
15
Second Semester
STAT 482 Capstone Course in
Statistics
Statistics elective7
Outside specialization elective6
Elective hours4
(Th-Pr)
(3-0)
Cr
3
3
3
4
13
Notes:
1. Two lower-level science courses are to be selected from ASTR 111; BIOL 111; BIOL 112; CHEM
2.
3.
4.
5.
6.
7.
101/111 or CHEM 103/CHEM 113; CHEM 102/CHEM 112 or CHEM 104/CHEM 114; PHYS
208; PHYS 218. A third science course is to be selected from any course satisfying the life and
physical sciences requirement for the University Core Curriculum.
Select 8 hours from CSCE 110, CSCE 111, CSCE 121, or CSCE 206.
Select 3 hours from COMM 203, COMM 205, or COMM 243, which fulfills the communication
requirement for the University Core Curriculum.
Three elective hours must be chosen from the approved University Core Curriculum list for language,
philosophy and culture, three elective hours must be chosen from the approved University Core
Curriculum list for creative arts, and three elective hours must be chosen from the approved University
Core Curriculum list for social and behavior sciences. In addition, 6 hours of courses must be in the
area of international and cultural diversity. These may be in addition to University Core Curriculum
courses, or if a course in this category satisfies an area or the Core, it can be used to meet both
requirements.
Students must take at least one course from the following courses: MATH 220, MATH 308, MATH
409, MATH 410, MATH 417 or MATH 437, MATH 442, MATH 446, MATH 447, MATH 469, ISEN
420, ISEN 421, ISEN 424. The student must take a total of at least 12 hours of mathematics and statistics
elective courses.
Students must take 12 hours in an outside specialization area upon approval by a departmental advisor.
At least 6 hours must be upper level hours.
Students must take at least two courses from the following courses: STAT 407, STAT 426, STAT 436,
STAT 438, STAT 445, STAT 446, STAT 459, STAT 485, STAT 489, STAT 491, ISEN 314. The
student must take a total of at least 12 hours of mathematics and statistics elective courses.
*If a grade of D or F is earned in any of the following courses, MATH 151/MATH 171, MATH 152/MATH
172, MATH 221/MATH 251/MATH 253, MATH 220, MATH 323, MATH 308, STAT 211, or STAT 212,
this course must be immediately retaken and a grade of C or better earned. The department will allow at most
two D’s in upper-level (325-499) courses. If a third D is earned, one of the three courses in which a D was earned
must be retaken and a grade of C or better earned.
121
APPENDIX D.
Postdoctoral Training Program in Biostatistics, Bioinformatics and the Biological Basis of
Nutrition and Cancer
Director: Raymond J. Carroll
In 2001, the Department of Statistics was awarded A National Cancer Institute (NCI) R25T grant (CA-R25T090301:
Postdoctoral Training Program in Biostatistics, Bioinformatics and the Biological Basis of Nutrition and Cancer, Raymond J.
Carroll, P.I.). This multidisciplinary grant included investigators from the Department of Statistics, the Department of
Electrical and Computer Engineering, and the Faculty of Nutrition. The associate director of the grant, Dr. Nancy Turner, is
now a professor in the Department of Nutrition and Food Sciences. Department of Statistics mentors have included Bani
Mallick, Jianhua Huang, Alan Dabney, Marina Vannucci, and Naisyin Wang.
The Program has received $500,000 per year in direct costs, and has also had substantial matching funds from the
College of Science, the College of Engineering, and the College of Agriculture and Life Sciences.
The purpose of the grant was to train postdoctoral statisticians and electrical engineers on the role of nutrition in
cancer development. The 6 investigators in Nutrition, all lab-based biochemists, serve as mentors for all trainees. The trainees
first visit 3 laboratories for a month each, and then select a mentor for the rest of their time in the program. They spend
approximately 20% of their time physically in the lab of their nutrition mentors and are provided offices within the
Department of Statistics or the Department of Electrical and Computer Engineering.
The trainees spend 2-3 years in the program, and there are 4 trainees in any given year. NCI requires all trainees to
be U.S. citizens or permanent residents. To date, there have been 26 trainees, including current ones. They are listed below.
Most of them left the program with at least one first-authored paper in a nutrition or cancer journal. The substantial direct
exposure to a lab means that many of the trainees have a very deep understanding of the biological issues around nutrition
and cancer, and the technologies associated with them.
The Program was renewed in 2006 and 2011, with almost perfect scores each time. These scores reflect that the
trainees are actually contributing to our understanding of nutrition and cancer. We had every expectation of renewal in 2016,
but unfortunately the NCI withdrew the Program Announcement in 2013, and there is no possibility of submitting a renewal.
We are contemplating submitting a “renewal” but for the only mechanism possible, a T32, although the amount of funding
available to support postdocs via a T32 is much less than for the R25T. There is also a possibility that the Cancer Prevention
Institute of Texas (CPRIT), a State of Texas agency, will announce a competition for training programs.
122
Current and Past Trainees
Trainee
Aniruddha Datta
Danh Nguyen
Qi Zheng
Mahlet Tadesse
Kimberly Drews
Wenjiang Fu
Ivan Ivanov
Michael Swartz
Erchin Serpedin
Sujay Datta
Lan Zhou
Ann Chen
Xiaoning Qian
Ivan Zorych
Yuliya Kaprievitch
Scott Schwartz
Nikolay Bliznyuk
Carmen Tekwe
Tanya Garcia
Xiangfang Li
Maria Joseph
Amin Zollanvari
Roger Zoh
Houssein Assaad
Daniel Mohsenizadeh
Mathew McLean
Ph.D.
University of Southern California
UC Davis, California
Texas A&M University
Harvard University
Texas Tech University
University of Toronto
University of South Florida
Rice University
University of Virginia
University of Connecticut
University of California
Medical University of S. Carolina
Yale University
Rutgers University
Medical University of S. Carolina
Duke University
Cornell University
University of Buffalo
Texas A&M University
Rutgers University
Iowa State University
Texas A&M University
Iowa State University
The University of Texas at Dallas
Texas A&M University
Cornell University
Current Title
J.W. Runyon, Jr. ’35 Professor II
Professor
Associate Professor
Associate Professor
Associate Research Professor
Professor
Clinical Associate Professor
Assistant Professor
Professor
Associate Professor
Associate Professor
Assistant Member
Assistant Professor
Unknown
Lecturer
Research Associate
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Senior Statistician
Assistant Professor
Research Assistant Professor
Research Assistant Professor
Research Assistant Professor
Research Assistant Professor
Current Employment
TAMU Electrical & Computer Engineering
University of California, Irvine Medical School
TAMU School of Public Health
Georgetown College
George Washington University
University of Houston
TAMU, School of Veterinary Medicine
University of Texas, School of Public Health
TAMU Electrical and Computer Engineering
University of Akron
TAMU Department of Statistics
Moffitt Cancer Center
University of South Florida
Recently at Columbia University with D. Madigan
University of Tasmania
University of Texas, Austin
University of Florida
TAMU School of Public Health
TAMU School of Public Health
Prairie View A&M University
General Dynamics Information Technology
Electronic Engineering Istanbul Kemerburgaz University
TAMU School of Public Health
STATA Corporation
TAMU Electrical and Computer Engineering
TAMU Department of Statistics
123
APPENDIX E.
Institute for Applied Mathematics and Computational Science (IAMCS) and the Department of
Statistics
The Institute for Applied Mathematics and Computational Science (IAMCS) was founded in 2008 with James A.
Calvin (Statistics) as the Director. The IAMCS received substantial funding for a 6-year contract from the King Abdullah
University of Science and Technology in Saudi Arabia (KAUST), the only western style university in that country. In 2010
Dr. Calvin took a position at KAUST, and Raymond J. Carroll became the new Director, a position he still holds.
The IAMCS had members from many colleges in the University, particularly the College of Science, the College of
Engineering and the College of Geosciences. The great majority of the initial members were from the Departments of
Statistics, Mathematics and Computer Science and Engineering. In Statistics, the members have included Bani Mallick,
Jianhua Huang, Valen Johnson, Suojin Wang, Marc Genton, Faming Liang, Mikyoung Jun, Huiyan Sang and Yanyuan Ma.
Coincidental with the KAUST contract, the IAMCS also participated in a university-wide competition to select senior
hires. Our group, called Applied Mathematics, Statistics and Computer Science (AMSCS), were winners of this competition,
and we commenced searches in each of the 3 named departments. The Statistics hire was Valen Johnson, now Head of the
Department of Statistics. The AMSCS program is funded by the Office of the Provost, which provides funding for a staff
member to run the day-to-day details of IAMCS, along with a small amount of funding for activities such as workshops,
invited speakers, etc.
Through its own funds, the IAMCS sponsors or co-funds workshops, invited speakers, visitors and events. In the current
2014-2015 fiscal year, the IAMCS has supported the following workshops.
•
Workshop on fractional differential equations: inverse problems, modeling and numerical analysis
•
Workshop on spatial statistics
•
Workshop on inverse problems and spectral theory
•
Workshop on computational fluid dynamics
IAMCS is also hosting a reception for Alain Goriely from the University of Oxford, who is giving a Department of
Mathematics Frontiers in Mathematics Lecture Series. Dr. Goriely also was the Director of a KAUST-funded Center.
124
Talks and Conferences funded by IAMCS
Date
Title
Organizer/Speaker
9/10/10
10/13/10
10/18/10
10/21/10
11/4/10
Taxonomy for the Automated Tuning of Matrix Algebra Software
Using Algebraic Multi-grid for Numerical Upscaling
On Steady and Unsteady Flows of Implicitly Constituted Incompressible Fluids
Alignment of LC-MS Proteomics Datasets Using Internal Anchors
Fast Algorithms for Analyzing Large Collections of Evolutionary Trees
Adaptive Anisotropic Meshing and Level Set for Free Surface and Interface
Flow Problems
Disease-Induced Juvenile Mortality and Transient and Asymptotic Population
Dynamics of Chinook Salmon
Spatiotemporal modeling of Mortality Risks using P-Splines: An Application
to Brain Cancer
Predicting Radiating Shock Experiments
Modeling of Magnetic Shape Memory Alloys
ADI Method for Sylvester Equations
Detecting Small Low Emission Sources on a Large Random Background
Elizabeth R. Jessup
Panayot S. Vassilevski
Joseph Malek
Alan Dabney
Tiffani Williams
11/17/10
11/18/10
11/30/10
12/2/10
1/20/11
1/28/11
2/2/11
2/3/11
2/17/11
2/17/11
2/23-24/11
3/2/11
3/24/11
3/28/11
3/31/11
4/4/11
4/7/11
4/25/11
4/26/11
5/2/11
5/20-21/11
5/23-27/11
5/31-31/11
8/26/11
9/8/11
9/10-11/11
9/22/11
Performance Characteristics of Hybrid MPI/Open MP Implementations of
NAS Parallel Benchmarks SP and BT on Large-Scale Cray XT and Blue
Gene/P Supercomputers
Estimation of the Drag Coefficient Using the Oceans Responses to a Hurricane:
A Data Assimilation Approach
Surveillance for Emerging Space-Time Clusters
Visualization in Biomedial Computation
Integrated Second Generation Sequencing and Microarray Based Analyses to
Identify Genetic Variants
First Steps of Coupling 2D and 3D Models for Lake Simulations
Discontinuous Petrov-Galerkin Method for Steady Transport
New Methods for Avian Distribution and Abundance Estimation
Pathway Regulatory Analysis and Modeling of Drug Intervention Effects in the
Context of Bayesian Networks
Global Sub-Micrometer-Level Survey of the Mouse Brain Microstructures Using
the Knife-Edge Scanning Microscope
Multilevel Methods for Nonconforming FEM Systems
Coupling Water-Column Bio-Optics and Coral Reef Ecology to Predict Impacts
of Climate Change and Coastal Zone Development
Modern C++ Design for Modern Computer Architectures: Meta Programming
for Higher Performance Computing
Statistical Inverse Problems in the Biosciences
Applied Inverse Problems Conference
3rd Annual Spring Symposium
Construction of High Order Schemes for the Compressible Euler and
Navier-Stokes Equations
Massively Parallel Finite Element Simulations with Application to Convection
in the Earth’s Mantle
Ecosystem Modeling, Simulation and Assessment Workshop
Interrogating Genomes Through Next Generation Sequencing
Thierry Coupez
Masami Fujiwara
Lola Ugarte
Ryan McClarren
Dimitris Lagoudas
Ren-Cang Li
Peter Kuchment
Xingfu Wu
Sarah Zedler
Renato Assuncao
Guy Almes, John Keyser,
Wolfgang Bangerth, Bani Mallick
Scott Dindot
Barbell Janssen
Victor Calo
Bret Collier
Ivan Ivanov
Yoonsuck Choe
Svetozar Margenov
Daniel Roelke
Joel Falcou
Yanyuan Ma, Raymond Carroll
Bill Rundell
IAMCS
Remi Abgrall
Timo Heister
Daniel Roelke
Scott Dindot
125
9/26/11
10/6/11
10/27/11
11/3/11
11/17/11
12/7/11
1/26/12
2/16/12
2/21/12
3/1/12
3/3/12
3/5/12
3/6/12
3/8/12
3/19/12
3/22/12
4/4/12
4/5-6/12
4/6/12
4/12/12
4/24/12
5/6-8/12
5/8-9/12
7/19/12
8/2/12
8/9/12
9/20/12
10/4/12
10/12-13/12
10/18/12
10/29/12
11/1/12
11/28/12
11/28/12
12/10/12
2/7/13
3/7/13
3/22/13
3/28/13
Statistical Methods for Exploring Metabolic Networks
Stochastic Trojan Y-Chromosome Models for Eradication of Invasive Fish
Composing Parallel Applications Using Paragraphs
Parallel Finite Elements Earthquake Rupture Simulations on Large-Scale
Multicore Supercomputers
Coupled Global-Regional Data Assimilation with an Ensemble-based Approach
Variance Reduction Methods in Stochastic Homogenization
Joint High-dimensional Bayesian Variable and Covariance Selection with an
Application to eQTL Analysis
Identifying Mechanistic Similarities in Drug Responses
Implicit-explicit Runge-Kutta Methods with Stabilized Finite Elements for
Advection-diffusion Equations
Research Topics in Quantitative Population Ecology
Sparsity Constraint in Electrical Impedance Tomography:
Complete Electrode Model
Robust Parameter Mesh-Free Preconditioner for a Boundary Control Elliptic
Fekete-Gauss Spectral Elements with Application to Navier-Stokes flows
Computer Model Calibration with High and Low Fidelity Model Output for
Spatio-Temporal Data
A Bayesian Framework for the Solution of High-Dimensional Stochastic PDEs
The Effect of a Surface Tension on the Stress Field near a Curvilinear Crack
Joint Asymptotics and Inferences for Partly Linear Models
Computational Biomedicine & Geophysics Workshop
Bootstraping Independent Component Analysis
Nonstationary Cross-covariance Models for Multivariate Processes on a Globe
Optimal Design, Resonance and Bandgap Formation in Goupillaud-type
Elastic Media
4th Annual Spring Symposium
Modeling and Simulation of Wave Propagation and Applications@KAUST
Adaptive Wavelets for Uncertainty Quantification in Dynamical Systems
Efficient Estimation of Dynamics Density Functions with an Application
to Outlier Detection
Computational Electromagnetics Laboratory at KAUST and Development of
Exact Absorbing Boundary Conditions There
Local Properties of Irregularly Observed Gaussian Fields
Visual Cortical Response Power Law and Perceptual Thresholding
Climate Science and Spatial Statistics
Environmental Effect on Egress Simulation
Understanding Soot Growth Turbulent Nonpremixed Glame via Direct
Numerical Simulation and Lagrangian Statistics
The STAPL Parallel Graph Library
Adaptive Graph Regularized Nonnegative Matrix Factorization via
Feather Selection
Joint Estimation of Multiple Bivariate Densities of Protein Backbone Angles
Using an Adaptive Exponential Spline Family
An Axiomatic and Data Driven View on the EPK Paradox
Transmission-Recovery Tradeoff in Mathematical Modeling of
Infectious Diseases
The Probability of a Salmonellosis Outbreak on a Grower-Finisher Pig Farm
Parallel Programming with R
A Framework for Scalable Parameter Estimation of Gene Circuuit Models Using
Structural Information
Erkki Somersalo
Xueying Wang
Timmie Smith
Xingfu Wu
Istvan Szunyogh
Frederic Legoll
Anindya Bhadra
Ivan Ivanov
Alexandre Ern
Masami Fujiwara
Matthias Gehre
Marcus Sarkis
Richard Pasquetti
William Kleiber
Nicholas J. Zarabas
Anna Zemlyanova
Guang Cheng
Jay Walton
Zhuqing Yu
Mikyoung Jun
George Gazonas
IAMCS
Yalchin Efendiev, Victor Calo
Denis Dreano
Abdulhakim Qahtan
Kostyantyn Sirenko
Myoungji Lee
Yoonsuck Choe
Huiyan Sang, Mikyoung Jun
Sam Rodriguez
Fabrizio Bisetti
Harshvardhan
Jingyan Wang
Mehdi Maadooliat
Maria Grith
Renata Ivanek
Glenn Lahodny
Xingfu Wu
Xin Gao
126
4/5/13
4/8/13
4/18/13
5/2/13
5/12-13/13
9/4/13
11/15/13
1/21/14
1/23/14
2/4/14
2/5/14
2/6/14
2/18/14
2/25/14
2/27/14
Intro: Parallel Programming With R
Modern Trends in High Performance Computing
STAPL
Scalable, Incremental Learning with MapReduce Parallelization for Cell
Detection in High-Resolution 3D
5th Annual Spring Symposium
TAMU Interdisciplinary Lecture Series- How Texas Plans for and
Responds to Drought
Simulation and Statistics in Graphics
IAMCS Machine Learning & Applied Statistics Workshop Series- The
Impoverishment of Scientific Education
IAMCS Machine Learning & Applied Statistics Workshop Series- Statistical
Inference for Massic Distributed Spatial Data using Low-Rank Models
IAMCS Machine Learning & Applied Statistics Workshop Series- Text Analytics
Synergizing Electromagnetic and Seismic Techniques for Enhanced Reservoir
History Matching via Data Assimilation Techniques
Workshop on Fractional Differential Equations: Inverse Problems, Modeling
and Numerical Analysis
IAMCS Machine Learning & Applied Statistics Workshop Series- Authoring
Packages for the R Programming Language
IAMCS Machine Learning & Applied Statistics Workshop Series- Tools for
Reproducible Research and Dynamic Documents with R
Arid Zone Hydrology under Climate Change Scenarios for the 21st Century
10/17-19/14
IAMCS Machine Learning & Applied Statistics Workshop Series- Invitation to
Multidisciplinary Research and the Geospatial Science and Technology Center
IAMCS Machine Learning & Applied Statistics Workshop SeriesA Flexible Semiparametric Approach to Model, Measure and Improve
Sales Agency Productivity
IAMCS Machine Learning & Applied Statistics Workshop Series- Modeling and
Predicting Atlantic Hurricane Activity
IAMCS Machine Learning & Applied Statistics Workshop Series- Dimension
Reduction: A Semiparametric Approach, Estimation, Inference, and Efficiency
IAMCS Machine Learning & Applied Statistics Workshop Series- An Overview
of Frequent Model Averaging
IAMCS Machine Learning & Applied Statistics Workshop Series- Tensor
Decompositions and Sparse Log-linear Models
IAMCS Machine Learning & Applied Statistics Workshop Series- A Class of
Matern-like Covariance functions for smooth processes on a sphere
IAMCS Machine Learning & Applied Statistics Workshop Series- A Prediction
Divergence Criterion for Model Selection
IAMCS Machine Learning & Applied Statistics Workshop SeriesThreshold Generalized Principal Component Regression: Forecasting
with Many Predictors
Inverse Problems and Spectral Theory
4/8/15
Computational Fluid Dynamics
3/20/14
3/25/14
4/1/14
4/3/14
4/8/14
4/8/14
4/15/14
4/22/14
4/24/14
1/29/15
Workshop on Spatial Statistics
Xingfu Wu
E.N. (Mootaz) Elnozahy
Nathan Thomas
Chul Sung
IAMCS
Brenner Brown
John Keyser
Edward R. Dougherty
Matthias Katzfuss
Edward Jones
Klemens Katterbauer
Meriem Laleg, Raytcho Lazarov,
Bill Rundell
Mathew McLean
Mathew McLean
Binayak Mohanty
Matthew McCabe
Michael P. Bishop
Venkatesh Shankar
Ramalingam Saravanan
Yanyuan Ma
Xinyu Zhang
Anirban Bhattacharya
Mikyoung Jun
Maria-Pia Victoria-Feser
Mohsen Pourahmadi
G. Berkolaiko
Mikyoung Jun, Matthias
Katzfuss, Huiyan Sang
Jean-Luc Guermond, Andrea
Bonito, Bojan Popov
127
APPENDIX F.
Center for Statistical Bioinformatics
The Center was approved by the Board of Regents in March, 2007. Its mission was to serve as a focus for
activities in Bioinformatics that were of a statistical nature. Given the great interest in Bioinformatics, including at
least one White paper included in the final list, the mission of the Center remains critical.
There is no budget for the Center, whose activities are supported by individual funds. The Center’s main
activities are to host visitors and run seminars that are open to the entire university committee. We announce all talks
via our web site, broadcast mailings, and through the Alliance for Bioinformatics, Computational Biology and Systems
Biology. Our activities are done in coordination with the NCI-funded R25T Training Program in Biostatistics,
Bioinformatics and Nutrition. We need some university support to make this center more active and competitive.
Current Members of the Center
Bani K Mallick (Director)
Raymond Carroll
Alan Dabney
David Dahl
Aniruddha Datta
Edward Dougherty
Ruzong Fan
Ivan Ivanov
Faming Liang
Jeff Hart
Samiran Sinha
Cliff Spiegelman
128
APPENDIX G.
Statistics Gifts and Endowments
Original
Endowment/Gift
Description
Margaret Sheather Memorial
$26,150
Award given to the best Master’s Project
Ronald R Hocking Endowment
Lecture
$50,000
Conference - Hocking Lecturer Series
Emanuel & Carol Parzen Innovation
$28,285
Conference and Honorarium Award
Raymond Carroll Young Investigator
$37,101
Conference and Honorarium Award
$1,000,000 (planned)
Chair in Statistics
Roland H Acra '86
$25,000
Award given to the best Master’s Project in Analytics
Eva L. & Lee H Smith Endowment
$25,000
Scholarship payment toward tuition
Ruth & Howard Newton Memorial
$25,738
Scholarship payment toward tuition
STAT Former Student Fellowship
$26,028
Scholarship payment toward tuition
Norbert Hartmann, Jr.
$50,500
Scholarship payment toward tuition
Anant Kshirsager Endowment
$100,000
Scholarship payment toward tuition
James C. Goodlett '67
$24,983
Scholarship payment toward tuition
George P. Mitchell ’40 Chair
$1,000,000
Chair in Statistics
SAS Gift to M.S. Analytics
$1,000,000
Gift to the Analytics Program
$1,750,000 (planned)
Gift to the Department
Name
Jill & Stuart Harlin '83 Chair
Norbert Hartman Legacy Gift
129
APPENDIX H.
Spring 2009 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
DATE
Alyson G. Wilson
Iowa State University
Statistical Challenges from Science-Based Stockpile Stewardship
January 22
Elvezio Ronchetti
University of Geneva
A New Robust and Accurate Test for Generalized Linear Models
January 29
Olga Savchuck
TAMU Statistics
Choosing a Kernel for Cross-Validation
February 3
Sushasini Subba Rao
TAMU Statistics
What to Do When the Standard Assumptions in a Multiple Linear
Regression are Not Satisfied
February 10
Akihiko Inoue
Hokkaido University
Lue Ping Zhao
Fred Hutchinson Cancer
Research Center
Joseph Tadjuidje Kamgaing
University of Kaiserslautern
Dynamics of Indifference Prices Derived from Optimal
Intertemporal Risk Allocations
February 12
From Genes, to Gnome, and to Sequences-A Statistician’s
Perspective
February 19
Switching Regimes Autoregressive Driven Processes Versus Hidden
Markov Models
February 26
Conditional U-Statistics with Applications in Discriminant Analysis,
ARMA Processes and Hidden Markov Models
March 5
Control Variates for Reversible MCMC Samplers
March 12
Testing for General Fractional Integration in the Time Domain
March 26
Modeling Correlation in Longitudinal Data
March 31
David S. Stoffer
University of Pittsburgh
Spectral Magic
April 2
Kate Calder
Ohio State University
Kernal-Based Models for Space-Time Data
April 9
Huiyang Sang
TAMU Statistics
Bayesian Hierarchial Models: Two Case Studies
April 15
Hira L. Koul
Michigan State University
Model Diagnostics Via Khmaladze’s Martingale Transform
April 16
Emanuel Parzen
TAMU Statistics
A Last Lecture 1949-2009: Quantiles are “Optimal”
April 23
Pierre Pinson
Technical Univ. of Denmark
Regime –Switching Dynamics of Short-Term Wind Power
Fluctuations
April 30
Mandy Hering
Texas A&M University
Comparing Accuracy of Spatial Forecasts
June 30
Kostas Fokianos
University of Cyprus
On Poisson Autoregression
July 28
Madan L. Puri
University of Texas, Arlington
Petros Dellaportas
Athens Univ. of Economics &
Business
Uwe Hassler
Goethe Univ, Frankfurt am
Main
Mohsen Pourahmadi
TAMU Statistics
130
Fall 2009 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
DATE
Deepak K. Agarwal
Yahoo Research
Recommender System for Web Applications
September 10
Adin-Cristian Andrei
A Novel Pseudo-Observations-Based Modeling Approach for
University of Wisconsin, Madison Interval-Censored Data
Anindya Roy
University of Maryland,
Predicting False Discovery Proportion Using Mixture Models
Baltimore County
David B. Dahl
Distance-Based Probability Distribution on Set Partitions for
Texas A&M University
Bayesian Nonparametric Models
September 17
September 24
September 30
Alexander Aue
University of California, Davis
A Point Process Model for Transaction-Level Asset Prices
October 1
Zhaosong Lu
Simon Fraser University
An Augmented Lagrangian Approach for Sparse Principal
Component Analysis
October 8
Zhaohai Li
George Washington University
Potential Impact of Population Structure on Population-Based
Case-Control Association Studies
October 15
Samiran Sinha
Texas A&M University
Victor De Oliveira
University of Texas, San
Antonio
Michael Akritas
Pennsylvania State University
Analysis of Cohort Studies with Multivariate, Partially Observed
Disease Classification Data
October 20
Optimal Predictive Inference in Log-Gaussian Random Fields
October 22
Fully Nonparametric Mixed Effects Models: Testing for the Fixed
Main Effect
October 29
Hwan-Sik Choi
Texas A&M University
Model Selection Testing for Diffusion Processes with Applications
to Interest Rate and Exchange Rate Models
November 5
Sanat K. Sarkar
Temple University
Controlling Different Error Rates in Multiple Testing: Some
Recent Developments
November 12
Mikyoung Jun
Texas A&M University
Stephan Morgenthaler
Ecole Polytechnique Federale
de Lausanne
Samuel Kou
Harvard University
Nonstationary Covariance Models for Processes on a Sphere
November 18
Variance Stabilized Statistical Tests
November 19
Multi-Resolution Inference of Stochastic Models from Partially
Observed Data
December 1
Wei-Biao Wu
University of Chicago
Simultaneous Inference of Time-Varying Linear Models
December 3
131
Spring 2010 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
DATE
Brian Hartman
TAMU Grad Student
From Argentina to Zimbabwe: Where Should I See My
Widgets?
January 14
David E. Tyler
State University of New Jersey
Invariant Coordinate Selection: A New Method for Exploring
Multivariate Data
January 21
James G. Scott
University of Texas at Austin
The Horseshoe Prior and Its Connection With Bayesian
Nonparametrics
January 28
Wei-Biao Wu
University of Chicago
Simultaneous Inference of Time-Varying Linear Models
February 4
Adarsh Joshi
TAMU Grad Student
Objective Bayesian Model Selection for High-Dimensional
High-Throughput Data
February 9
Ori Rosen
University of Texas, El Paso
Bayesian Mixtures of Autoregressive Models
February 11
Ingrid Van Keilegom
Université catholique de Louvain
Univariate Frontier Estimation in the Presence of Measurement
Error
February 18
Arka P. Ghosh
Iowa State University
Optimal Control of a Stochastic Network Driven by a
Fractional Brownian Motion Input
February 25
Jeff Hart
Texas A&M University
Recent Research
March 2
T. Siva Tian
University of Houston
FUNER: A Novel Approach for the EEG/MEG Inverse
Problem
March 4
Hira Koul
Michigan State University
Model Diagnostics via Khmaladze’s Martingale Transform
March 11
Roger Koenker
University of Illinois
Beyond the Average Man: Additive Models for Conditional
Quantiles
March 24
Michael S. Smith
University of Melbourne, Australia
Bayesian Skew Selection for Multivariate Models
April 1
Regina Liu (Hartley Lectures)
Rutgers University
Statistics is a Many-Splendored Thing: Mining Massive Text
Data and Beyond
April 5
Regina Liu (Hartley Lectures)
Rutgers University
Data Depth for Multivariate Spacings, Ordering, Tolerance
Regions, etc.
April 6
Regina Liu (Hartley Lectures)
Rutgers University
DD-Classifiers: New Nonparametric Classification Procedures
April 7
Faming Liang
Texas A&M University
An Overview of Markov Chain Monte Carlo Methods
April 7
Li-Ping Zhu
East China Normal University
Model-Free Dimension-Reduction for Ultrahigh Dimensional
Data
April 8
Thick-Pen Transformation for Time Series
April 15
Ying Nian Wu
Univ of California, Los Angeles
From Wavelet Sparse Coding to Visual Pattern Modeling
April 22
Jeremy Taylor
University of Michigan
Joint Longitudinal-Survival Models and their Application in
Prostate Cancer
April 29
Piotr Fryzlewicz
London Sch. of Econ & Political Sci.
132
Fall 2010 Colloquium & Seminar Speakers
NAME
Tao Shi
Ohio State University
Dan Glab
Texas A&M University
Michael Stein
University of Chicago
Marc Genton
Texas A&M University
Li Gan
Texas A&M University,
Economics
Evarist Giné
University of Connecticut
Genevera I. Allen
Baylor University/Rice University
Huaiqing Wu
Iowa State University
Dale Zimmerman
University of Iowa
Yanyuan Ma
Texas A&M University
Ji Zhu
University of Michigan
Byungtae Seo
Texas Tech University
Carlos M. Carvalho
University of Texas
Bo Li
Purdue University
Wolfgang Polonik
University of California, Davis
TITLE OF ABSTRACT
DATE
Statistical Modeling of Airs Level 3 Quantization Date
September 9
Testing Lack-of-Fit of Generalized Linear Models via Laplace
Approximation
An Extension of Power Law Generalized Covariance
Functions to the Space-Time Setting
September 15
September 16
A Sample of Current Research in Spatial Statistics
September 21
A Simple Test of Private Information in the Insurance
Markets with Heterogeneous Insurance Demand
September 23
Some Aspects of Density Estimation: Sup-Norm Loss,
Adaptivity to Smoothness, Spatial Adaptivity
September 30
Modeling Transposable Data
October 7
A Prediction-Based Model Selection Approach
October 14
The Joys of Geocoding (from a Spatial Statistician’s
Perspective)
Semiparametrics in Generalized Linear Latent Variable Model
and More
October 21
October 27
Extracting Communities from Networks
October 28
Inconsistent MLS with Incomplete Data
November 4
Dynamic Stock Selection Strategies: A Structures Factor
Model Framework
November 11
The Value of Multiproxy Reconstruction of Past Climate
November 18
Testing for Modality, Residual Empirical Process and
Weighted Sums for Time Varying Processes
December 2
133
Spring 2011 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
Ehsan S. Soofi
Sample Information about the Parameter and Parameter and
University of Wisconsin-Milwauke Prediction, and Predictability of Stochastic Process
DATE
January 20
Nikolay Bliznyuk
Texas A&M University
Renato Assunção
Univ. Federal de Minas Gerais,
Brasil
Xiao-Li Meng
Harvard University
Boaz Nadler
Weizmann Institute of Sci.,
Israel
Wolfgang Härdle
Humboldt-Universität zu Berlin
Nonlinear Latent Process Models for Integrating SpatioTemporal Exposure Data from Multiple Sources
January 27
Surveillance for Emerging Space-Time Clusters
February 17
What’s the H in H-Likelihood: A Holy Grail or an Achilles’
Heel?
February 24
Detection of Signals in Noise, Matrix Perturbation and
Random Matrix Theory
March 3
Pricing of Asian Temperature Risk
March 24
Jeffrey D. Hart
Texas A&M University
Brown Bag Lecture Series/ “A Hodgepodge of Statistics
Problems”
March 30
Clifford Spiegelman
Texas A&M University
A Nonparametric Approach Based on a Markov Like Property
for Classification
March 31
Pradeep Ravikumar
University of Texas, Austin
Dirty Statistical Models: M-Estimators and High-Dimensional
Analysis
April 7
Arne Bathke
University of Kentucky
Nonparametric Methods for Multivariate Data and Repeated
Measures Design
April 14
Yuanjia Wang
Columbia University
Deborah Nolan
University of California,
Berkeley
Analysis of Multilevel Genetic and Medical Studies by
Penalized Splines: Marginal versus Conditional Approach
April 21
New Development in R for Information Visualization
April 28
134
Fall 2011 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
DATE
Christopher Field
Dalhousie University
Bootstrapping Robust Hierarchical Models
September 8
David Hitchcock
University of South Carolina
Limited-Information Modeling of Loggerhead Turtle
Population Size
September 15
Michele Guindani
MD Anderson Cancer Center
Generalized Species Sampling Priors with Latent Beta
Reinforcements
September 22
Jean Opsomer
Colorado State University
Analytic Inference for Data from Complex Surveys
September 29
Emanuel Parzen
Texas A&M University
Classification of High Dimensional Data, Fundamental
Statistical Methods
October 6
Karabi Nandy
Univ. of California, Los Angeles
Optimal Designs for Non-Monotone Dose-Response Models
October 13
Peng Qiu
MD Anderson Cancer Center
Understanding Cellular Heterogeneity Using Single-Cell
Cytometric Data
October 20
Dongseok Choi
Oregon Health & Sci. University
Detecting Subclusters in Outliers
October 27
Kai-Sheng Song
University of North Texas
Peng Wei
Univ. of Texas Sch. Public
Health
Marc A. Suchard
Univ. of California, Los Angeles
Nonparametric Estimation of Roc Curve Via Bernstein
Expansion and Non-Asymptotic Order Selection
November 3
Network-Based Statistical Methods for Genetic and Genomic
Data
November 10
Ridiculously Parallel, Serial Algorithms for Statistical Inference
November 14
Samuel Müeller
University of Sydney, Australia
Graphical Tools for Model Selection
November 17
Bani K. Mallick
Texas A&M University
Bayesian Inference and Uncertainty Quantification in Large
Scale Inverse Problems
December 1
Len Stefanski
North Carolina State University
Research Agenda 2012-2014
December 12
135
Spring 2012 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
DATE
Scott Holan
University of Missouri
Bayesian Multiscale Multiple Imputation with Implications for
Data Confidentiality
January 19
Ke-Li Xu
Texas A&M University
Powerful Tests for Structural Changes in Volatility
February 2
Mauro Gasparini
Politecnico di Torini, Italy
Statistical Issues in the Analysis of Count Emg Data from a
Study on Obstetric Trauma During Delivery
February 9
Xihong Lin
Harvard School of Public Health
Wilfredo Palma
Pontificia Universidad Catolica
de Chile
Emanuel Parzen
Texas A&M University
Xinwei Deng
Virginia Polytechnic Institute
and State University
William Kleiber
National Center for Atmospheric
Center
Scott Crawford
Texas A&M University
Hypothesis Testing for High Dimensional Data: Studying Rare
Variant Effects in Sequencing Association Studies
February 16
Estimation and Prediction of Locally Stationary Time Series
February 23
Workshop on “History of Statistics”
February 29
Penalized Covariance Matrix Estimation Using A MatrixLogarithm Transformation
March 1
Computer Model Calibration With High and Low Fidelity
Model Output for Spatial Temporal Data
March 8
Efficient Estimation in a Regression Model with Missing
Responses
March 21
Haiyan Wang
Kansas State University
Yuedong Wang
Univ. of California, Santa
Barbara
Richard Levine
San Diego State University
Nonparametric Variable Selection in High Dimensional Data
for Classification
March 22
Basis Selection from Multiple Libraries
March 29
Bayesian Survival Trees for Clustered Observations, Applied
to Tooth Prognosis
April 5
A Frequency Domain Empirical Likelihood Method for
Irregularly Spaced Spatial Data
April 12
Bayesian Semiparametric Analysis for Two-Phase Studies of
Gene-Environment Interaction
April 19
Principal Components of Cumulants
April 26
Multivariate Quantile and Outlyingness Functions
April 27
Soutir Bandyopadhyay
Lehigh University
Jaeil Ahn
Univ. of Texas, MD Anderson
Cancer Center
Lek-Heng Lim
University of Chicago
Robert Serfling
University of Texas, Dallas
136
Fall 2012 Colloquium & Seminar Speakers
NAME
Kristin Lennox
Lawrence Livermore National
Laboratory
Dipanker Bandyopadhyay
University of Minnesota
TITLE OF ABSTRACT
DATE
A Bayesian Measurement Error Model for Misaligned
Radiographic Data
September 7
Semiparametric Spatial Models for Periodontal Disease Data
with Non-Random Missingness
September 14
Stanislav Volgushev
Ruhr-Universität Bochum
Marc Hallin
Princeton University & Université
libre de Bruxelles
Momiao Xiong
University of Texas Health
Science Center at Houston
Steven Rutkowski
ESPN College Recruiter
Caspar Ammann
National Center for Atmospheric
Research
Val Johnson
Texas A&M University
Empirical and Sequential Empirical Copula Processes Under
Serial Dependence and Weak Smoothness Conditions
September 21
Of Copulas, Quantiles, Ranks, and Spectra an L1-Approach to
Spectral Analysis
September 28
Genetic Studies of Complex Diseases in the Sequence Era
October 5
Job Opportunities and Descriptions of Statisticians at ESPN
October 7
From Climate Science to Climate Science Applications –
Uncertainty and Other Challenges in Making Climate Model
Simulations Useful
October 12
Why Should Someone be Bayesian?
October 18
Ping Li
Cornell University
Bigdata: Probabilistic Methods for Efficient Search and
Statistical Learning in Extremely High-Dimensional Data
October 19
Avishek Chakraborty
Texas A&M University
Nonstationary Models for Uncertainty Quantification in
Physical Systems
November 2
Alan Fieberson
NASA Scientist
Lie Wang
Massachusetts Inst of
Technology
Jeffrey D. Hart
Texas A&M University
Job Opportunities at NASA, Research Fields and Various
Collaboration
November 7
Tiger: A Tuning-Intensive Approach for Optimally Estimating
Large Undirected Graphs
November 9
Testing Equality of a Large Number of Densities
November 16
Kathryn Roeder
Carnegie Mellon University
Next Generation Sequencing and the Genetic Risk of Autism
November 30
137
Spring 2013 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
DATE
Ian McKeague
Columbia University
Adaptive Resampling for Detecting the Presence of Significant
Predictors
January 18
Anirban Bhattacharya
Duke University
Bayesian Shrinkage
January 22
Ani Eloyan
Johns Hopkins University
Likelihood Based Population Independent Component Analysis
January 25
Lingzhou Xue
Princeton University
Regularized Learning of High-Dimensional Sparse Graphical
Models
January 29
Pavel Krivitsky
Penn State University
Modeling Dynamic Networks in Changing Populations Based
on Static Egocentrically-Sampled Data
February 5
Matthew Reimherr
University of Chicago
Association Studies with Functional Phenotypes
February 8
Matthias Katzfuss
Universität Heidelberg, Germany
Low-Rank Spatial and Spatio-Temporal Models for Large
Datasets
February 12
James Long
University of California, Berkeley
Classification of Sparse, Irregularly Sampled Time Series and
Feature Measurement Error
February 19
Andreas Artemiou
Sufficient Dimension Reduction Through Inverse Regression
Michigan Technological University and Machine Learning
February 22
Michael Schweinberger
Penn State University
Second-Generation Exponential-Family Models of Networks:
Scaling Up
March 1
Chae Young Lim
Michigan State University
Clustering Cancer Mortality Curves of U.S. States Based on
Change Points
March 8
Murali Haran
Penn State University
Yu Shen
UT M.D. Anderson Cancer
Center
Daniel B. Rowe
Marquette University
Dimension Reduction and Alleviation of Confounding for
Spatial Generalized Linear Mixed Models
March 22
Statistical Challenges and Promises when Sampling Bias is
Present
March 25
Proper Statistical Modeling of Complex-Valued FMRI Data
April 5
Variance Estimation for Regression Models
April 12
Zhezhen Jin
Columbia University
Daikwon Han
Texas A&M Health Science
Center
Adrian E. Raftery
University of Washington
Integrating Geographic Information Systems and Spatial
Methods into Epidemiologic Research: Opportunities and
Challenges
Bayesian Reconstruction of Past Populations for Developing
and Developed Countries
April 19
April 26
138
Fall 2013 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
DATE
Ching-Kang Ing
Academia Sinica
Orthogonal Greedy Algorithm and High-Dimensional Akaike’s
Information Criterion
August 30
Jianhua Huang
Texas A&M University
Some Examples of Regularized Matrix Decomposition
September 6
Mary C. Meyer
Colorado State University
Variable and Shape Selection in the Generalized Additive
September 13
Guosheng Yin
University of Hong Kong
Heterogeneous Feature Screening in Ultrahigh Dimensional
Data
September 20
♦Robert Cezeaux, Nathanial Litton
Capital One
Working as a Statistician in Financial Services Industry and at
Capital One
September 25
Xin Qi
Georgia State University
Restricted Local Polynomial Fitting and Parameter Estimation
in ODE and PDE
September 27
♦Roy Parsons
Dell
Review of Dell Global Services Engineering Organization and
Ph.D Internship Opportunities
October 7
Dennis K.J. Lin
Pennsylvania State University
Dimensional Analysis and Its Applications in Statistics
October 11
♦Yanyuan Ma
Texas A&M University, Statistics
Workshop on Semiparametric Efficiency
October 17
Eric C. Chi
Rice University
Some Recent Developments and Applications of the MM
Algorithm
October 18
Chuanhua Liu
Purdue University
Exact Prior-Free Probabilistic Inference: The Inferential Model
Approach
October 25
Bing Li
Pennsylvania State University
Anthea Monod
Technicon - Israel Institute of
Technology
Michael Daniels
University of Texas at Austin
On an Additive Semi-Graphoid Model for Statistical Networks
with Application to Pathway Analysis
November 1
Estimating Thresholding Levels for Random Fields via Euler
Characteristics
November 8
A Bayesian Nonparametric Approach to Monotone Missing
Data in Longitudinal Studies with Informative Missingness
November 15
Henrik Schmiediche
Henrik Talks Tech: A Workshop on Computing Resources
Texas A&M University, Statistics
Clifford Spiegelman
Texas A&M University, Statistics
JFK Assassination: Chemistry, Metallurgy, and Statistics
William A. Tobin
Increase Doubt About Lone Gunman Theory
Forensic Engineering
International
♦Statistics Graduate Student Association (SGSA) Seminar/Event
November 20
November 22
139
Spring 2014 Colloquium & Seminar Speakers
NAME
TITLE OF ABSTRACT
DATE
Brad Efron
Stanford University
Frequentist Accuracy of Bayesian Estimates
January 24
Yuval Benjamini
Stanford University
Learning About the Visual Cortex From Predictive Models
January 31
Mario Peruggia
Ohio State University
Bayesian Synthesis and Clustered Bayesian Model Averaging
February 7
A New Nonparametric Stationarity Test of Time Series in
Time Domain
February 14
DeMix: Deconvolution for Mixed Cancer Transcriptomes
Using Raw Measured Data
February 21
Experiences During the Job Search Process
February 25
Nonparametric Models for Data Subject to Shape Constraints
February 28
Suojin Wang
Texas A&M University
Wenyi Wang
University of Texas, MD Anderson
Cancer Center
♦ Anirban Bhattacharya
♦ Matthias Katzfuss
♦ James Long
Texas A&M University
Sujit Ghosh
North Carolina State University
Debdeep Pati
Florida State University
Rui Tuo
Chinese Academy of Sciences
Georgia Institute of Technology
Linglong Kong
University of Alberta
Bayesian Model Based Shape Clustering
March 7
A Theoretical Framework for Calibration in Computer
Models: Parametrization, Estimation and Convergence
Properties
March 21
Spatially Varying Coefficient Model for Neuroimaging Data
March 28
Steven MacEachern
Ohio State University
The Blended Paradigm: A Bayesian Approach to Handling
Outliers and Misspecified Models
April 4
Jiashun Jin
Graphlet Screening for Rare and Weak Signals
Carnegie Mellon University
Stéphane Guerrier
Wavelet Variance Based Estimation of Latent Time Series
University of California, Santa
Models
Barbara
Judea Pearl
University of California, Los
The Science of Cause and Effect
Angeles
♦Statistics Graduate Student Association (SGSA) Seminar/Event
April 11
April 25
May 9
140
Fall 2014 Colloquium & Seminar Speakers
SPEAKER
TITLE OF ABSTRACT
Hao Chen
University of California, Davis
Change-Point Detection for Multivariate and Object Data
September 5
William B. Tarinelli, Jr.
♦Travelers Insurance
Industry Recruiting: Advanced Analytics Development and
Internship Program
September 10
Eric Vance
(LISA) Virginia Tech
LISA 2020: Creating a Network of Statistical Collaboration
Laboratories
September 19
Qiongxia Song
University of Texas at Dallas
Minsuk Shin, Shahina Rahman,
Nan Zhang, Scott Goddard
♦Texas A&M Statistics
Val Johnson, Michael Longnecker,
Jianhua Huang
♦Texas A&M Statistics
Ana-Maria Staicu
North Carolina State University
Simultaneous Inference for the Mean of Functional Time
Series
September 26
Secrets to Success
September 26
Christopher Wikle
University of Missouri
Interaction-Based Parameterizations for Nonlinear Dynamic
Spatio-Temporal Statistical Models
Bayes for Big Ideas
Wasserstein Posteriors: Robust and Scalable Bayes
Bayes for Big Tables and Networks
October 13
October 14
October 15
A General Framework for Mixed Graphical Models
October 24
Jeffrey W. Miller
Duke University
Gary Beach, Ian Wilson, Jared
Harlow, Lucy Luo, Mike Davidson
♦ConocoPhillips
Trevor J. Hastie (2014 Parzen Prize)
Stanford University
Combinatorial Stochastic Processes for Variable-Dimension
Models
October 31
Industry Recruiting: Global New Ventures Exploration
(GNVE) and Geosciences & Reservoir Engineering (GRE)
November 5
Sparse Linear Models
November 6
Lorenzo Trippa
Harvard University
Bayesian Nonparametric Cross-Study Validation of Predictions
Methods
November 7
Nathaniel Litton, Robert Cezeaux
♦Capital One
Industry Recruiting: Analytics Program Recruitment
November 12
Jae-Kwang Kim
Duke University
Propensity-Score-Adjustment Method for Nonignorable
Nonresponse
November 14
David B. Dunson (Hartley Lectures)
Duke University
Genevera Allen
Rice University
DATE
Town Hall Meeting
October 2
Classical Testing in Functional Linear Models
October 3
October 10
Nancy Reid (ADVANCE Speaker Serie Approximate Likelihoods
University of Toronto
“The Whole Woman Thing”
November 17
November 18
Xiaoming Huo
Georgia Institute of Technology
Fast Computing for Statistical Dependency
November 21
Sharon Durham, Matt Witten,
Lance Pate ♦Rackspace
Industry Recruiting: Presentation from Data Science &
Analytics Leaders
December 3
Arnab Maity
North Carolina State University
Testing for Additivity in Nonparametric Regression
December 5
Jason D. Lee
● Stanford University
Teaching and Research Interests
December 17
♦Statistics Graduate Student Association (SGSA) Seminar/Event
● Faculty Recruiting Candidate
141
APPENDIX I.
Department of Statistics Alumni Advisory Board
In 2008 the Department of Statistics began an Alumni Advisory Board. This small group of alumni
provides guidance to the department on its current operations and future development. The current board
members, as well as those who have served in the past, were selected based on their outstanding graduate record
and on their continuing success in the field of statistics. Members of the Alumni Advisory Board are typically
invited to campus once or twice a year to meet with the department head and offer input on the direction of
departmental programs. The most recent board meeting was held on January 28, 2015. Agenda items discussed
were the Distance Learning Program, the M.S. in Analytics program, the Graduate Program, and the
Undergraduate Degree Proposal.
Below please find resumes for the following Alumni Advisory Board members: Ersen Arseven,
Christian Galindo, Marcy Johnson, Michael Kutner, Jeffrey Morris, and Scott Grimshaw.
142
ERSEN ARSEVEN
Ph.D. Statistical and Process Consultant
Clinical and Non-Clinical Drug Development
243 South Boulevard, Nyack, New York 10960-4114
Voice: 845-358-4636 Email: [email protected]
Overview of experience and accomplishments
I am a Ph.D. Statistical and Process Consultant with more than 35 years of successful clinical and non-clinical drug
development experience in eleven therapeutic areas with twelve NDAs. My Therapeutic area experience includes
cardiovascular diseases, gastrointestinal disorders, infectious diseases, oncology, ophthalmology, pulmonary diseases, sleep
disorders, vaccines, diagnostic agents, tuberculin diagnostic tests, medical devices and hospital products.
I developed my technical and management skills working at line and senior management positions in American and
European multinational pharmaceutical companies with worldwide responsibility for Statistics, Data & Document
Management, and Medical Systems for non-clinical and clinical drug development and registration.
I have developed a global outlook on the scientific, regulatory, and competitive market pressures facing the pharmaceutical
industry. Consulting with top-tier companies in the pharmaceutical and information technology industries further
enhanced the breadth and depth of my knowledge and experience, and has given me a wealth of practical and useful
insight into the discovery and development of biopharmaceutical/biotechnology products.
I have excellent technical knowledge, and very good people and interpersonal skills.
I make use of innovative and pragmatic approaches for sound operational staging of development projects and clinical
trials with optimal deployment of internal and external resources for faster development, approvals, and transition of new
drugs to marketing. Some highlights of my record of results:
• Excellent knowledge and experience in global development of drugs, biologicals, and contrast agents for
diagnostic imaging.
• Successfully prepared and obtained approval for twelve New Drug Applications (NDAs) for treatment of
hypertension, glaucoma, cardiovascular, pulmonary and infectious diseases, prophylactic vaccines, and contrast
agents for diagnostic use.
• Carried out Due Diligence investigation for a venture capitalist interested in acquiring drug product under
development by a small pharmaceutical company. Assessed the adequacy of the pre-clinical and clinical study
results and the clinical development plan in terms of whether they provided evidence for efficacy and safety
required by regulatory agencies.
• For a premier Biotechnology company with a very promising compound in development, evaluated completeness
of the company’s Drug Development Process (DDP), both in scope and depth, in conjunction with the
management and technical environment. Identified significant gaps. Made concrete recommendations for closing
identified gaps and laid out methods of implementation.
• For the same company, preparation of Common Technical Document (CTD) as the primary evaluation tool,
investigated how much progress the company had 2 made in filling gaps identified earlier. Scope of the analysis
covered the development and implementation of required drug development infrastructure, technology platforms,
applications, tools, and processes in Clinical Research, Non-Clinical Research, Pharmaceutical Sciences,
Production, and in Project Management departments.
• Directed multinational clinical development project to a successful completion by managing statistical, data
management, and programming work of the client company and its numerous European and American Clinical
Research Organization (CRO) development partners.
• Led team of international scientists of Fortune 20 information technology company in assessing commercial
potential of their new technologies – including product knowledge bases, data marts, and warehouse technologies
– and consulting services for use in the drug development process.
• Developed and implemented a uniform Biometrics Process that made use of “best industry practices” in a
decentralized multinational CRO with five independent Business Centers.
• Evaluated operations and infrastructure of two key departments of a mid-sized pharmaceutical company;
realigned the organizational structure, standardized clinical data processing and programming, and defined proper
technology and staff skill mix for efficient operation.
Professional Experience
143
Statistical and Process Consulting
May 1992-Present
Provides innovative and sound approaches to enable global development, registration,
and licensing of biopharmaceuticals, biologicals, diagnostic tests, and contrast agents.
Services offered include:
• Development of statistical design, analysis, presentation strategy, and methodologies. Implementation of strategy
for a specific product development and registration.
• Integration of scientific evidences for efficacy and safety summaries. Review and evaluation of clinical dossiers,
pre-clinical safety and CMC sections, integrated summaries, clinical trial reports, protocols, and methodologies.
• Due Diligence for licensing and investment decisions by companies and venture capitals.
o Evaluation and validation of pre-clinical and clinical study results and methodologies reported in
prospectus portfolios.
o Assessment of the quality of submitted work and its acceptability by regulatory agencies to establish safety
and efficacy.
• Project and resource management for operational staging of global clinical development projects.
• Management and organizational consulting for drug development process.
• Development of knowledge bases for therapeutic areas and for products to leverage knowledge accumulated
during the development phase to facilitate smooth transitioning of product from development team to marketing
team for more effective market introductions.
Schering-Plough Research Institute, Kenilworth, NJ
Statistics and Statistical Programming (02/2003-06/2005)
Director Non-Clinical Statistics
Directed activities of groups of statisticians that provided statistical design and analysis services to:
Discovery Research Division
Chemical and Pharmaceutical Sciences Division
Safety Sciences Division of the Research Institute
Prepared and reviewed statistical components of Chemistry-Manufacturing-Control (CMC) and Safety Sections of
regulatory submissions. In discussions with regulatory agencies, provided defense of statistical methodology and
conclusions.
Boehringer-Ingelheim Pharmaceuticals, Inc., Ridgefield, CT
Scientific Affairs Division (12/1990-05/1992)
Group Director with Worldwide Responsibility
For worldwide company, as a member of the International Medical Committee, evaluated the medical and operational
staging of global development projects. Managed the development and implementation of statistical design, analysis, and
data management of global projects. Led the design and implementation of processes to produce submissions dossiers
from standard components.
For U.S. operations unit, directed statistical design and analysis, data management, document processing, and archiving
services for the R&D and Medical Divisions. Directed development and implementation of systems and office automation
to enable effective functioning of Medical Affairs Division. Staff of 77 and budget of M$6.5.
Boehringer-Ingelheim Pharmaceuticals, Inc., Ridgefield, CT
Medical Affairs Division (05/1988-12/1990)
Director, Medical Data and Administrative Services
Directed the activities of seven departments in two divisions: Statistical Design and Analysis, Clinical Trial Information,
Clinical Trial Support, Medical Systems, Medical Planning and Budgets, Project Management, and Medical Grants and
Contracts. Directed development and implementation of systems and procedures to improve planning and control of
clinical drug development project activities and costs. Set information technology direction. Prepared and monitored the
Medical Affairs Division budget and expenses. Staff of 83 and budget of M$30.
Boehringer-Ingelheim Pharmaceuticals, Inc., Ridgefield, CT
Medical Affairs Division (07/1984-05/1988)
Director, Medical Data Services
144
Established effective Statistical Design and Analysis, Data Management, Document Management, and Medical Systems
Departments. Developed and implemented Biometric Process to enable global clinical development of our drugs ahead of
competitors. Led international task force to develop worldwide clinical data management procedures and standards.
Achieved and maintained a zero backlog in processing and analysis of clinical trial data through streamlining procedures,
upgrading professional staff, and implementation of proper information technology.
Directed four departments with staff of 65 and budget of M$4.5.
American Cyanamid Company, Pearl River, NY
Medical Research Division (04/1982-07/1984)
Group Leader, Non-Clinical Statistics
Managed group of Statisticians that provided statistical design and analysis services to:
Biological Discovery, Analytical Services, Pharmacodynamics and Pharmacokinetics, Process Development, Formulation,
Stability Testing, and Toxicology. Developed systems for Analysis of Toxicology Data and Quality Control of vaccine
production.
Boehringer-Ingelheim Pharmaceuticals, Inc., Ridgefield, CT
Medical Affairs Division (02/1978-03/1982)
Manager, Statistical Evaluation
Established the Statistical Design and Analysis Department. Served as company expert for defense of statistical
methodology and conclusions before regulatory agencies. Linked the activities of Clinical Research with R&D.
American Cyanamid Company, Pearl River, NY
Medical Research Division (01/1975-02/1978)
Research Statistician
Designed and analyzed clinical trials in anti-infectives, ocular hypertension, vaccines, and inhaled steroids. Designed and
implemented biological screens in drug discovery to identify potential drugs in targeted therapeutic areas. From these
screens, one anticancer compound, Mitoxantrone, was identified and successfully developed and marketed for treatment
of leukemia. 5
Education
Ph.D. 1974, Texas A&M University, College Station, Texas
Major: Statistics, emphasis on multivariate analysis, general linear models, design of experiments, and Markov
renewal processes. Minors: Operations Research and Mathematics. Dissertation title: Applications of Graph
Theory to PERT Critical Path Analysis.
M.A. 1969, University of Pennsylvania, Philadelphia, Pennsylvania.
Major: Economics
B.A. 1964, Ankara University, SBF, Ankara, Turkey.
Major: Economics and Finance
Professional Societies
American Association for the Advancement of Science
American Statistical Association
American Society for Quality
Institute for Mathematical Statistics
Biometrics Society
Pharmaceutical Manufacturers Association, Biostatistics Steering Committee, 1986-1989
Editorial Board Member, Biopharmaceutical Report, 1999-2001
Honors and Awards
• Appointed to the Alumni Advisory Board, Department of Statistics, Texas A&M University
• Inducted into the Academy of Distinguished Former Students of the College of Science, Texas A&M University
• Received H.O. Hartley Award for Distinguished Service to the Discipline of Statistics, Texas A&M, University
Department of Statistics
145
Publications and Technical Reports
• "Stationary State Probabilities of a Markov Renewal Process and Optimum Scores Associated with the States." A.
M. Kshirsagar and E. Arseven, Communication in Statistics, Volume 3 (10), 1974.
• "Note on the Equivalency of Two Discrimination Procedures." A. M. Kshirsagar and E. Arseven, American
Statistician, Volume 29 (1), 1975.
• “An Elementary Derivation of the Non-Central Chi-Square Density Function.” Ersen Arseven, Metron, Volume
33 (1-2), 1975.
• "Critical Path Analysis in Stochastic Networks: Statistical PERT." H. O. Hartley, R. L. Sielken, and E. Arseven,
SCIMA, Volume 6 (3), 1977.
• "Application of Graph Theory to PERT Critical Path Analysis." H. O. Hartley and E. Arseven, Technical Report
No. 46, Office of Naval Research, Project NR047-700.
• "Statistical Critical Path Analysis in Acyclic Stochastic Networks: Statistical PERT." H. O. Hartley, R. L. Sielken,
and E. Arseven, Office of Naval Research, Contract N00014-68-A-0140, Project NR047-700.
• Data Management. Medical Guide. Volume 1, Notes for Guidance on Operational Procedures within BoehringerIngelheim. E. Arseven, P. Reilly, A. Lawton, D. Piera, 1989.
Presentations
1. Lectures, Controversial Issues in Clinical Trials: Interim Analyses, Multi-Center Trials, Crossover Designs,
Combination Drug Testing, Dose Tolerance and Response Studies. Pharmaceutical Manufacturers Association
Workshops for New Clinical Statisticians in the Industry
Washington, D. C., May 9-10, 1988
Washington, D. C., March 6-7, 1989
2. From Compartmentalization to Integration: Requirements of Global Drug Development. Boehringer-Ingelheim
Worldwide Medical Directors' Meeting, Rudesheim, Germany, October 14-18, 1990.
3. Training Course in Non-Clinical Statistics. Course developer and leader. Pharmaceutical Manufacturers
Association Education & Research Institute. Washington, D. C., January 9-11, 1991.
4. “Reengineering of the Clinical Drug Development Process,” Invited paper on Total Quality Management in Drug
Development, American Statistical Association Winter Conference. Atlanta, Georgia, January 6-7, 1994.
5. “Have You Developed the Skills That Are Necessary for Your Success?” Group Discussion, American Statistical
Association Winter Conference, Raleigh, North Carolina, January 5-8, 1995.
6. “Interim Analysis in Clinical Trials,” Corning Besselaar, Inc. Statisticians’ Forum, Princeton, New Jersey,
November 13, 1996.
7. “Have You Developed the Skills Necessary for Your Success in the Pharmaceutical Industry?”
Biopharmaceuticals Section Roundtable Discussion Program, Joint Statistical Meetings, Baltimore, Maryland,
August 8-12, 1999.
8. "What Do Statistical Consultants Really Do?” Invited presentation to graduate students of Department of
Statistics at Texas A&M University, College Station, Texas, October 14,2002.
9. “Using Historical Control Data in Evaluating Tumor Trends for Oncogenicity Studies.” Amrik Shah and Ersen
Arseven. Harvard School of Public Health, Department of Biostatistics, Colloquium 2003-2003 Series, Boston,
April 24, 2003.
146
CHRISTIAN D. GALINDO
Ph.D. and Marketing Analytics, Facebook
2750 El Prado Road, Burlingame, California 94010
Voice: 415-484-6262 Email: [email protected]
OBJECTIVE
Executive-level position in consumer-based e-commerce, mobile, or social media, with a focus on business intelligence and
analytics.
QUALIFICATION
Quantitatively-focused senior professional with a doctorate in Statistics and a strong background in business intelligence,
strategy, and analytics across several industries including E-commerce, Search, Online Marketing, and Biotechnology.
Professional strengths include
• Reputation for strong analytics, objective business sense, and making data actionable.
• Talent for clear and concise explanations of complex quantitative concepts.
• Versatile background and skill set allowing for efficient collaboration across a broad range of corporate functional
areas.
• Passion for delivering accurate data and reporting to drive sound business decisions.
• Strongly held belief in being customer-focused for long term company success.
EXPERIENCE
Facebook
Menlo Park, California
MARKETING ANALYTICS
Build and lead the consumer marketing analytics practice
2014 – Present
Leap Commerce
San Francisco, California
2013 – 2014
VICE PRESIDENT – PRODUCT STRATEGY& ANALYTICS
Lead the Product, Marketing, and Analytics efforts of an early stage technology startup providing a SaaS social recommendation and discovery
solution.
• Develop a holistic point-of-view around the use of earned media to provide a marketing-led e- commerce
experience.
• Create both a strategic roadmap and individual product feature requirements around a set of enterprise solutions
that bring the power of word-of-mouth advertising down the purchase funnel from awareness and consideration
to engagement and sales.
• Spearhead marketing efforts to support venture fundraising, partnerships, and business development collateral.
• Oversee the algorithmic development of Leap’s recommendation engine.
Mode Media
Brisbane, California
2011-2013
VICE PRESIDENT, ANALYTICS
Own the Analytics function for the largest consumer lifestyle publishing network in the US and a Top 10 global web property.
• Developed and managed a centralized Analytics organization across Mode Media post Ning acquisition.
• Areas of analytics ownership include Advertising (Targeting, Measurement), Marketing (Channel,
MarCom, Product, Market Research), Product (Ad Platform, Subscription Platform, O&O, Consumer
& Publisher Products), and Business Intelligence (KPI Development & Reporting, Business Insights).
• Nurtured a quantitatively-driven business culture, so that decisions affecting strategy, plans, programs,
and customer experience were based on relevant data and insights.
• Responsible for responding to brand advertising targeting and measurement needs, and for working closely
with strategic data and research vendors to maintain and grow productive partnerships.
• Business owner of reporting, analytics, and KPIs that demonstrate how content and social media matter to
brands, consumers, publishers, and network creators; and how the interests of all constituents should be
aligned for long-term success.
• Assumed thought leadership role, both internally and within professional bodies such as the IAB, in defining
Social Data and articulating its use within an advertising framework.
• Continued to manage all facets of product, marketing, and business analytics for Ning.
Ning
Palo Alto, California
DIRECTOR, ANALYTICS
2010-2011
147
Oversaw the Data Engineering and Business Intelligence teams for the world’s largest social website platform, with over 100,000 subscribed
networks and 60 million monthly visitors. Acquired by Mode Media in 2011.
• Mentored, grew and led the Analytics team consisting of Data Engineers and Analysts.
• Worked closely with technical teams to ensure products were developed and launched with properly engineered
data, relevant tracking, performance metrics, and reporting in place.
• Guided the evolution of the company by analyzing customer behavior including website
performance, network trends, social engagement, marketing, and merchandising activity.
• Partnered with Marketing to establish sound measurement practices including channel attribution, program
measurement and marketing optimization.
• Drove the development of a simplified and unified data framework that served as the backbone for the
company's executive and operational dashboards.
Threadsy/Swaylo
San Francisco, California
2010
HEAD OF ANALYTICS (LONG-TERM CONTRACT)
Developed the analytics framework of an early-stage influence marketing start-up that used viral techniques to achieve a customer base of over
six million people. Acquired by Facebook in 2012.
• Oversaw business intelligence for the world's first integrated communications client – combining email, Twitter,
social networks, and 40 other web services into a unified communications experience
• Developed analytic framework to assess viral marketing performance and engagement of social network
applications built on “gamification” techniques.
• Helped drive development of highly viral Facebook applications, twice reaching AppData’s Top 20 and leading to
Swaylo’s current customer base.
Shopping.com
Brisbane, California
2005 – 2010
GLOBAL DIRECTOR, BUSINESS INTELLIGENCE
Head of Business Intelligence and Analytics for a multinational subsidiary of eBay, Inc., with a portfolio of websites attracting 25 million
monthly visitors and accounting for $1.5 billion in merchant sales annually.
• Directed company vision and strategy for business and product analytics.
•
•
•
•
•
Translated business needs into actionable and relevant data requirements. Managed business intelligence
as an enterprise product including tracking, collection, reporting, and analysis.
Developed and oversaw testing of new site features, and made recommendations for product
optimization. Investigated website performance throughout product lifecycle.
Maintained systemic view of site analytics, monitoring changes in operational behavior due to new product
initiatives, SEO/SEM marketing, distribution, and merchant deals.
Led pricing strategy to align financial interests of merchants and partners, optimize merchant ROI, increase
network quality, and enhance user experience. Major projects included regular rate-card evaluations, seasonal
pricing adjustments, the development of a dynamic CPC-based pricing methodology, and a refined revenue
attribution process for a CPA business model.
Conceptualized data structure and reporting required to reinvigorate community-based shopping program
that had been growing at 50 thousand members monthly.
LookSmart, Ltd.
San Francisco, California
2002 – 2005
MANAGER, SEARCH ANALYSIS
Formalized and executed a relevance assessment program across both the search engine and ad platforms for a syndicated search network
serving a half billion ad impressions daily.
• Managed analytics team in support of product strategies and marketing functions. Identified opportunities
to improve relevance and revenue through algorithmic development and alternative sales and business
development strategies.
• Devised novel approaches for evaluating search engine performance, including generalized between- list distance
metrics and distribution-free relevance measures. Informed testing methodology for such companies as MSN
and Inktomi.
• Drove the development of relevance scoring tools and optimized overall testing process.
• Consolidated data analysis onto one platform and generalized code to allow for scenario-based modeling. Reduced
testing timeframe and cost by 50%.
• Developed standards for relevance data storage, use, and analysis across R&D, Engineering, and
Architecture groups. Formulated automated relevance assessment methodology, allowing for regular,
efficient, and inexpensive product release feedback.
148
Coremetrics, Inc.
Burlingame, California
2000 – 2002
PRINCIPAL CONSULTANT, CLIENT ENGAGEMENT
Customer-facing role for the leading Software-as-a-Service web analytics and marketing optimization platform of its time. Founded
consulting practice that is still part of the core service offerings.
• Templatized and delivered consulting engagements designed to optimize client websites and online marketing
efforts. Oversaw the development and interpretation of advanced statistical models including such techniques as
discriminant analysis, factor analysis, cluster analysis, logistic and other nonlinear regression, CHAID, and CART.
• Developed training material for both internal and external consumption. Proposed advanced product offerings
based on industry needs and client feedback.
• Managed client relationship with numerous multi-channel customers such as Walmart, Columbia House, and
GMAC. Performed consulting engagements to guide online marketing efforts.
• Served as solutions engineer during customer sales cycle. Responsible for mapping business objectives
of potential clients to appropriate data collection and reporting.
Shockwave.com
San Francisco, California
2000
MARKET RESEARCH MANAGER / DATABASE MARKETING ANALYST
Managed consumer insights and marketing analytics for one of the Internet’s earliest video and gaming portals, with over 100 million registered
members worldwide.
• Functioned as statistical consultant and consumer behavior analyst while working with Content
Production, Programming, Site Development, Engineering, Marketing, Sales, and Business Development.
• Mined member database to research online behavior and attrition patterns. Implemented process for collection
and analysis of member demographics. Developed email marketing segmentation schemes for a program with a
monthly budget of $200,000.
• Managed primary research, including usability testing, focus groups, individual user behavior studies.
Implemented on-going customer satisfaction and loyalty studies. Maintained relations with secondary research
and external traffic vendors.
Genentech, Inc
South San Francisco, California
1998 – 2000
BIOSTATICIAN
Statistician supporting all stages of the drug development life cycle for the world’s largest and most successful biotechnology company.
• Supported nonclinical function through statistical consultation, experimental design, data analysis and
interpretation, and in-house training.. Served as primary statistical point-of-contact for over 500 scientists and
engineers in Research, Process Science, and Pharmacokinetics.
• Assumed biostatistical responsibilities in clinical drug development. Designed study protocols and analysis
plans, and monitored trials for statistical validity and compliance with federal regulations.
• Developed and taught company-wide statistics courses, and created a statistical resource website.
National Cancer Institute
Bethesda, Maryland
Summer 1997
STATISTICIAN
• Researched the estimation of disease penetrance, in particular testing a method for the determination of intrafamily phenotypic independence conditional on genotype.
Santa Monica, California
Summer 1996
The RAND Corporation
STATISTICAL CONSULTANT
• Analyzed Unites States Army logistics matters concerning overseas transportation of military equipment.
Formulated benchmarking criteria for present and future performance evaluations.
OTHER EXPERIENCE
The Deep End, 501(c)(3)
San Francisco, California
2007-Present
PRESIDENT
• President and lead financial officer of San Francisco Bay Area non-profit that produces events showcasing local
amateur electronic musicians and alternative artists, creates the annual large-scale Distrikt project at Burning
Man, and provides financial support to other charitable organizations and artists sharing a similar vision.
EDUCATION
Texas A&M University
College Station, Texas
• Doctor of Philosophy, Statistics
1998
149
•
Research Topic: Nonparametric inference, including mean functional estimation with missing data and confidence interval
construction for local estimating equations
Bachelor of Science, Summa Cum Laude, Applied Mathematical Sciences
1993
PUBLICATIONS
• Carroll, R. J. & Galindo, C. D. (1998). Measurement error, biases, and the validation of complex models for
blood lead levels in children. Environmental Health Perspectives. 106, 6: 1535-1539.
• Galindo, C. D. (1998). On nonparametric estimation of mean functionals. Statistics & Probability Letters. 39: 143149.
• Galindo, C. D., Liang, H., Kauermann, G., Carroll, R. J. (1999). Bootstrap confidence intervals for local
likelihood, local estimating equations, and varying coefficient models. January 2001.
150
MARCELLA M. JOHNSON
Director, Quantitative Research
Department of Biostatistics, University of Texas MD Anderson Cancer Center
3322 N. Braeswood Blvd., Houston, Texas 77025
Voice: 713-794-4193 Email: [email protected]
EDUCATION
Degree Granting Education:
Texas A&M University, College Station, TX, 1988, MS, Statistics
Texas A&M University, College Station, TX. 1986, BS, Applied Mathematical Sciences
EXPERIENCE/SERVICE
Academic Appointments:
• Director, Quantitative Research, Department of Biostatistics, Division of Quantitative Sciences, The University of Texas
MD Anderson Cancer Center, September 2008 – Present
• Associate Director, Quantitative Research, Department of Biostatistics, Division of Quantitative Sciences, The University of
Texas MD Anderson Cancer Center, March 2006 to August 2008
• Principal Statistical Analyst, Department of Biostatistics and Applied Mathematics, The University of Texas MD Anderson
Cancer Center, April 2004 to February 2006
• Senior Statistical Analyst, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, May 2001 to
March 2004.
• Manager, Patient Outcome Registry, Cyberonics, Inc., Houston, Texas, March 1999 to April 2001.
• Coordinating Manager, Biostatistics, Applied Logic Associates, Inc., Houston, Texas, October 1995 to February 1999.
• Manager, Biostatistics, Applied Logic Associates, Inc., Houston, Texas, August 1995 to October 1995.
• Senior Biostatistician, Applied Logic Associates, Inc., Houston, Texas, February 1994 to August 1995.
• Biostatistician, Applied Logic Associates, Inc., Houston, Texas, April 1992 to February 1994.
• Statistical Analyst, Physiological Research Group, KRUG Life Sciences, Inc., Houston, Texas, April 1990 to April 1992.
• Senior Research Assistant and Assistant Project Manager, Coordinating Center for Clinical Trials, School of Public Health,
University of Texas Health Science Center, Houston, Texas, May 1998 to April 1990.
• Statistical Intern, Department of Biostatistics, Scott & White Memorial Hospital, Temple, Texas, August 1987 to May 1988.
Institutional Committee Activities:
- The University of Texas MD Anderson Cancer Center, Institutional Review Board, Associate Member, April 2012 –
present
- The University of Texas MD Anderson Cancer Center, Clinical Research Committee, September 2005 – present
- The University of Texas MD Anderson Cancer Center, Quality Improvement Oversight Committee, October 2007 –
August 2010
Other Appointments/Responsibilities:
- American Joint Committee on Cancer (AJCC) Melanoma Staging Committee (for development of the 7th Edition, Cancer
Staging Manual), September 2005 – March 2009
Consultantships:
- Cyberonics, Inc., Houston, Texas, January 2002- January 2006
RESEARCH
Grants and Contracts:
Funded Grants:
• Statistician, 20% salary support, NIH/NCI, 2 P30 CA016672 38: Cancer Center Support Grant – Biostatistics Resource
Group (PI: DePinho), 7/01/2013 - 6/30/2018, $635,606
PUBLICATIONS:
Articles in Peer-Reviewed Journals:
1. Gayed I, Vu T, Johnson M, Macapinlac H, Podoloff D. Comparison of Bone and 2-Deoxy-2-[18F]Fluoro-D-Glucose
Positron Emission Tomography in the Evaluation of Bony Metastases in Lung Cancer. Mol Imaging Biol. 2003 JanFeb;5(1):26-31.
2. Wierda WG, Johnson MM, Do KA, Manshouri T, Dey A, O'Brien S, Giles FJ, Kantarjian H, Thomas D, Faderl S, Lerner
S, Keating M, Albitar M. Plasma Interleukin 8 Level Predicts for Survival in Chronic Lymphocytic Leukemia. Br J
Haematol. 2003 Feb;120(3):452-6.
151
3. Do KA, Johnson MM, Doherty DA, Lee JJ, Wu XF, Dong Q, Hong WK, Khuri FR, Fu KK, Spitz MR. Second Primary
Tumors in Patients with Upper Aerodigestive Tract Cancers: Joint Effects of Smoking and Alcohol. Cancer Causes
Control. 2003 Mar;14(2):131-8.
4. Rousseau DL, Ross MI, Johnson MM, Prieto VG, Lee JE, Mansfield PF, Gershenwald JE. Revised American Joint
Committee on Cancer Staging Criteria Accurately Predict Sentinel Lymph Node Positivity in Clinically Node-Negative
Melanoma Patients. Ann Surg Oncol. 2003 Jun;10(5):569-74.
5. Prieto VG, Argenyi ZB, Barnhill RL, Duray PH, Elenitsas R, From L, Guitart J, Horenstein MG, Ming ME, Piepkorn
MW, Rabkin MS, Reed JA, Selim MA, Trotter MJ, Johnson MM, Shea CR. Are en face frozen sections accurate for
diagnosing margin status in melanocytic lesions? Am J Clin Pathol. 2003 Aug;120(2):203-8.
6. Ellerhorst JA, Cooksley CD, Broemeling L, Johnson MM, Grimm EA. High Prevalence of Hypothyroidism Among
Patients with Cutaneous Melanoma. Oncol Rep. 2003 Sep-Oct;10(5):1317-20.
7. Giles FJ, Vose JM, Do KA, Johnson MM, Manshouri T, Bociek G, Bierman PJ, O’Brien SM, Keating MJ, Kantarjian
HM, Armitage JO, Albitar M. Circulating CD20 and CD52 in patients with non-Hodgkin’s Lymphoma or Hodgkin’s
disease. Br J Haematol. 2003 Dec;123(5):850-857.
8. Raad I, Hanna HA, Alakech B, Chatzinikolaou I, Johnson MM, Tarrand J. Differential Time to Positivity: A Useful
Method for Diagnosing Catheter-related Bloodstream Infections. Ann Intern Med. 2004 Jan 6;140(1):18-25.
18
9. Gayed I, Vu T, Iyer R, Johnson M, Macapinlac H, Swanston N, Podoloff D. The Role of F-FDG PET in Staging and
Early Prediction of Response to Therapy of Recurrent Gastrointestinal Stromal Tumors, J Nucl Med. 2004; 45(1): 17-21.
10. Simeone AM, Li YJ, Broemeling LD, Johnson MM, Tuna M, Tari AM. Cyclooxygenase-2 is Essential for HER2/neu to
Suppress N-(4-Hydroxyphenyl) retinamide Apoptotic Effects in Breast Cancer Cells. Cancer Res. 2004, Feb 15; 64(4):
1224-8.
11. Kim KB, Sanguino AM, Hodges C, Papadopoulos NE, Eton O, Camacho LH, Broemeling LD, Johnson MM, Ballo MT,
Ross MI, Gershenwald JE, Lee JE, Mansfield PF, Prieto VG, Bedikian AY. Biochemotherapy in Patients with Metastatic
Anorectal Mucosal Melanoma. Cancer. 2004 Apr 1;100(7):1478-83.
12. Yang WT, Whitman GJ, Johnson MM, Bolanos-Clark M, Kushwaha AC, Hunt KK, Dempsey PJ. Needle Localization
for Excisional Biopsy of Breast Lesions: Comparison of Effect of Use of Full-field Digital Versus Screen-film
Mammographic Guidance on Procedure Time. Radiology. 2004 Apr;231(1):277-81.
13. Wu X, Zhao H, Do KA, Johnson MM, Dong J, Hong WK, Spitz MR. Serum Levels Of Insulin Growth Factor (IGF-I)
And IGF-Binding Protein Predict Risk Of Second Primary Tumors In Patients With Head And Neck Cancer, Clin
Cancer Res. 2004 Jun 15;10:3988-95.
14. Giles FJ, Vose JM, Do KA, Johnson MM, Manshouri T, Bociek G, Bierman PJ, O'Brien SM, Kantarjian HM, Armitage
JO, Albitar M. Clinical Relevance of Circulating Angiogenic Factors in Patients with Non-Hodgkin's Lymphoma or
Hodgkin's Lymphoma. Leuk Res. 2004 Jun;28(6):595-604.
15. Ellerhorst JA, Naderi AA, Johnson MK, Pelletier P, Prieto VG, Diwan AH, Johnson MM, Gunn DC, Yekell S, Grimm
EA. Expression of Thyrotropin-Releasing Hormone by Human Melanoma & Nevi. Clin Cancer Res. 2004 Aug
15;10(16):5531-6.
16. Albitar M, Do KA, Johnson MM, Giles FJ, Jilani I, O'Brien S, Cortes J, Thomas D, Rassenti LZ, Kipps TJ, Kantarjian
HM, Keating M. Free Circulating Soluble CD52 as a Tumor Marker in Chronic Lymphocytic Leukemia and Its
Implication in Therapy With Anti-CD52 Antibodies. Cancer. 2004 Sep 1;101(5):999-1008.
17. Wallace MJ, Jean JL, Gupta S, Eapen GA, Johnson MM, Ahrar K, Madoff DC, Morello FA, Murthy R, Hicks ME. Use of
Inferior Vena Caval Filters and Survival in Patients with Malignancy. Cancer. 2004 Oct 15;101(8):1902-7.
18. Do KA, Johnson MM, Lee JJ, Wu XF, Dong Q, Hong WK, Khuri FR, Spitz MR. Longitudinal Study of Smoking
Patterns in Relation to the Development of Smoking-Related Secondary Primary Tumors in Patients with Upper
Aerodigestive Tract Malignancies. Cancer. 2004 Dec 15;101(12):2837-42.
19. Choi H, Charnsangavej C, Faria Sde C, Tamm EP, Benjamin RS, Johnson MM, Macapinlac HA, Podoloff DA. CT
Evaluation of the Response of Gastrointestinal Stromal Tumors After Imatinib Mesylate Treatment: A Quantitative
Analysis Correlated with FDG PET Findings. Am J Roentgenol. 2004 Dec; 183(6):1619-28.
20. Simeone AM, Deng CX, Kelloff GJ, Steele VE, Johnson MM, Tari AM. N-(4-Hydroxyphenyl) Retinamide Is More
Potent Than Other Phenylretinamides in Inhibiting the Growth of BRCA1-Mutated Breast Cancer Cells. Carcinogenesis.
2005 May;26(5):1000-7.
21. Pawlik TM, Ross MI, Johnson MM, Schacherer CW, McClain DM, Mansfield PF, Lee JE, Cormier JN, Gershenwald JE.
Predictors and Natural History of In-Transit Melanoma After Sentinel Lymphadenectomy. Ann Surg Oncol. 2005.
12(8):587-96.
22. Gupta S, Johnson MM, Murthy R, Ahrar K, Wallace MJ, Madoff DC, McRae SE, Hicks ME, Rao S, Vauthey JN, Ajani
JA, Yao JC. Hepatic Arterial Embolization and Chemoembolization for the Treatment of Patients with Metastatic
Neuroendocrine Tumors. Cancer. 2005 Oct 15;104(8):1590-602.
23. Faderl S, Do KA, Johnson MM, Keating M, O'brien S, Jilani I, Ferrajoli A, Ravandi-Kashani F, Aguilar C, Dey A,
Thomas DA, Giles FJ, Kantarjian HM, Albitar M. Angiogenic Factors may have a Different Prognostic Role in Adult
Acute Lymphoblastic Leukemia (ALL), Blood. 2005 Dec 15;106(13):4303-7.
24. Berger AJ, Davis DW, Tellez C, Prieto VG, Gershenwald JE, Johnson MM, Rimm DL, Bar-Eli M. Automated
152
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
quantitative analysis of activator protein-2alpha subcellular expression in melanoma tissue microarrays correlates with
survival prediction. Cancer Res. 2005 Dec 1;65(23):11185-92.
Feng J, Lenihan DJ, Johnson MM, Karri V, Reddy CVR. Cardiac Sequelae in Brooklyn After the September 11 Terrorist
Attacks, Clin Cardiol. 2006 Jan;29(1):13-7.
Pawlik TM, Ross MI, Prieto VG, Ballo MT, Johnson MM, Mansfield PF, Lee JE, Cormier JN, Gershenwald JE.
Assessment of the role of sentinel lymph node biopsy for primary cutaneous desmoplastic melanoma. Cancer. 2006 Feb
15;106(4):900-6.
Ludwick JJ, Rossmann SN, Johnson MM, Edmonds JL. The Bacteriostatic Properties of Ear Tubes Made of Absorbable
Polylactic Acid, Int J Pediatr Otorhinolaryngol. 2006 Mar;70(3):407-10.
Simeone A, Colella S, Krahe R, Johnson MM, Mora E, Tari AM. N-(4-Hydroxyphenyl) retinamide and nitric oxide prodrugs exhibit apoptotic and anti-invasive effects against bone metastatic breast cancer cells. Carcinogenesis. 2006
Mar;27(3):568-77.
Aloia T, Gershenwald JE, Ross MI, Lee JE, Johnson MM, Cormier JN, Ng C, Mansfield PF. Utility of Computed
Tomography and Magnetic Resonance Staging Prior to Completion Lymphadenectomy in Patients with Sentinel Lymph
Node-Positive Melanoma. J Clin Oncol. 2006 Jun 20;24(18):2858-65.
Ellerhorst JA, Ekmekcioglu S, Johnson MK, Cooke CP, Johnson MM, Grimm EA. Regulation of iNOS by the p44/42
Mitogen-Activated Protein Kinase Pathway in Human Melanoma. Oncogene. 2006 Jun 29;25(28):3956-62.
Ekmekcioglu S, Ellerhorst JA, Prieto VG, Johnson MM, Broemeling LD, Grimm EA. Tumor iNOS predicts poor
survival for stage III melanoma patients. Int J Cancer. 2006 Aug 15;119(4):861-6.
Westney OL, Scott S, Wood CG, Eddings T, Johnson MM, Taylor JM, MCguire E, Pisters LL. Suburethral Sling at the
Time of Radical Prostectomy in Patients at High risk for Postoperative Incontinence. BJU Int. 2006 Aug;98(2):308-13.
Gannon CJ, Rousseau DL, Ross MI, Johnson MM, Lee JE, Mansfield PF, Cormier JN, Prieto VG, Gershenwald JE.
Accuracy of lymphatic mapping and sentinel lymph node biopsy after previous wide local excision in patients with
primary melanoma. Cancer 2006 Dec 1;107(11):2647-52.
Prieto VG, Mourad-Zeidan AA, Melnikova V, Johnson MM, Lopez A, Diwan AH, Lazar AJF, Shen SS, Zhang PS, Reed
JA, Gershenwald JE, Raz A, Bar-Eli M. Galectin-3 Expression Is Associated with Tumor Progression and Pattern of Sun
Exposure in Melanoma. Clin Cancer Res. 2006 12: 6709-6715.
Albitar M, Vose JM, Johnson MM, Do KA, Day A, Jilani I, Kantarjian H, Keating M, O'Brien SM, Verstovsek S,
Armitage JO, Giles FJ. Clinical relevance of soluble HLA-I and beta2-microglobulin levels in non-Hodgkin's lymphoma
and Hodgkin's disease. Leuk Res. 2007 Feb;31(2):139-45.
Tellez CS, Davis DW, Praetor VG, Gershenwald JE, Johnson MM, McCarty M, Bar-Eli M. Quantitative Analysis of
Melanocytic Tissue Array Reveals Inverse Correlation between Activator Protein-2alpha and Protease-Activated
Receptor-1 Expression during Melanoma Progression. J Invest Dermatol. 2007 Feb;127(2):387-93.
Burjonroppa SC, Tong AT, Xiao LC, Johnson MM, Yusuf SW, Lenihan DJ. Cancer patients with markedly elevated Btype natriuretic peptide may not have volume overload. Am J Clin Oncol. 2007 Jun;30(3):287-93.
Chakravarti N, Lotan R, Diwan AH, Warneke CL, Johnson MM, Prieto VG. Decreased Expression of Retinoid Receptors
in Melanoma: Entailment in Tumorigenesis and Prognosis. Clin Cancer Res. 2007. 13:4817-4824.
Mathew P, Thall PF, Bucana CD, Oh WK, Morris MJ, Jones DM, Johnson MM, Wen S, Pagliaro LC, Tannir NM, Tu
SM, Meluch AA, Smith L, Cohen L, Kim SJ, Troncoso P, Fidler IJ, Logothetis CJ. Platelet-Derived Growth Factor
Receptor Inhibition and Chemotherapy for Castration-Resistant Prostate Cancer with Bone Metastases, Clin Cancer Res.
2007. 13(19):5816-24.
Bedikian AY, Johnson MM, Warneke CL, Papadopoulos N, Hwu WJ, Kim K, Hwu P. Systemic Therapy for
Unresectable Metastatic Melanoma: Impact of Biochemotherapy on Long-term Survival. J Immunotoxicol. 2008
Apr;5(2):201-7.
Simeone AM, McMurtry V, Nieves-Alicea R, Saavedra JE, Keefer LK, Johnson MM, Tari AM. TIMP-2 Mediates the AntiInvasive Effects of the Nitric Oxide-Releasing Prodrug JS-K in Breast Cancer Cells. Breast Cancer Research,
2008;10(3):R44. Epub 2008 May 12.
Hoff AO, Toth BB, Altundag K, Johnson MM, Warneke CL, Hu M, Nooka A, Sayegh G, Guarneri V, Desrouleaux K,
Cui J, Adamus A, Gagel RF, Hortobagyi GN. The Frequency and Risk Factors Associated with Osteonecrosis of the Jaw
in Cancer Patients Treated with Intravenous Bisphosphonates. J Bone Miner Res. 2008 Jun;23(6):826-36. Epub 2008 Feb
5.
Bedikian AY, Johnson MM, Warneke CL, Papadopoulos NE, Kim K, Hwu WJ, McIntyre S, Hwu P. Prognostic Factors
that Determine the Long-term Survival of Patients with Unresectable Metastatic Melanoma, Cancer Invest. 2008
Jul;26(6):624-33.
Gershenwald JE, Andtbacka RHI, Prieto VG, Johnson MM, Diwan AH, Lee JE, Mansfield PF, Cormier JN, Schacherer
CW, Ross MI. Microscopic Tumor Burden in Sentinel Lymph Nodes Predicts Synchronous Nonsentinel Lymph Node
Involvement in Patients with Melanoma. J Clin Oncol. 2008 Sep 10;26(26):4296-303. Epub 2008 Jul 7.
Kim KB, Eton O, Davis DW, Frazier ML, McConkey DJ, Diwan AH, Papadopoulos NE, Bedikian AY, Camacho LH,
Ross MI, Cormier JN, Gershenwald JE, Lee JE, Mansfield PF, Billings LA, Ng CS, Charnsangavej C, Bar-Eli M, Johnson
MM, Murgo AJ, Prieto VG. Phase II Trial of Imatinib Mesylate in patients with metastatic melanoma. Brit J Cancer. 2008
Sep 2;99(5):734-40. Epub 2008 Aug 19.
153
46. Braiteh F, Soriano AO, Garcia-Manero G, Hong D, Johnson MM, Silva LdeP, Yang H, Alexander S, Wolff J, Kurzrock
R. Phase I Study of Epigenetic Modulation with 5-Azacytidine and Valproic Acid in Patients with Advanced Cancers. Clin
Cancer Res. 2008 Oct 1;14(19):6296-301.
47. Greene VR, Johnson MM, Grimm EA, Ellerhorst JA. Frequencies of NRAS and BRAF Mutations Increase from the
Radial to the Vertical Growth Phase in Cutaneous Melanoma, J Invest Dermatol. 2009 Jun;129(6):1483-8.
48. Zafar GI, Grimm EA, Wei W, Johnson MM, Ellerhorst JA. Genetic Deficiency of Complement Isoforms C4A or C4B
Predicts Improved Survival of Metastatic Renal Cell Carcinoma. J Urol. 2009 Mar;181(3):1028-34.
49. Petersson F, Diwan AH, Ivan D, Gershenwald JE, Johnson MM, Harrell R, Prieto VG. Immunohistochemical Detection
of Lymphovascular Invasion with D2-40 in Melanoma Correlates with Sentinel Lymph Node Status, Metastasis and
Survival. J Cutan Pathol. 2009: 36: 1157–1163.
50. Tu SM, Lopez A, Leibovici D, Bilen MA, Evliyaoglu F, General RD, Aparicio A, Pagliaro LC, Guo CC, Kuban DA,
Johnson MM, Logothetis CJ, Lin SH, PistersLL. Ductal Adenocarcinoma of the Prostate – Clinical Features and
Implications after Local Therapy. Cancer. 2009 Jul 1;115(13):2872-80.
51. Tu SM, Jones D, Mathew P, Johnson MM, Wong FC, Logothetis C. Phase I Study Of Concurrent Weekly Docetaxel And
Repeated 153sm-Lexidronam In Patients With Androgen-Independent Prostate Cancer. J Clin Oncol. 2009 Jul
10;27(20):3319-24.
52. Kim KB, Legha SS, Gonzalez R, Anderson CM, Johnson MM, Liu P, Papadopoulos NE, Eton O, Plager C, Buzaid AC,
Prieto VG, Hwu WJ, Roe AM, Alvarado G, Hwu P, Ross MI, Gershenwald JE, Lee JE, Mansfield, PF, Benjamin RS,
Bedikian AY. A Randomized Phase III Trial of Biochemotherapy versus Interferon-alpha-2b for Adjuvant Therapy in
Patients at High Risk for Melanoma Recurrence. Melanoma Res. 2009 Feb;19(1):42-9.
53. Jonasch E, Corn P, Pagliaro L, Warneke CL, Johnson MM, Tamboli P, Ng C, Aparicio A, Ashe R, Wright JJ, Tannir N.
Upfront Randomized phase II trial of sorafenib versus sorafenib and low-dose interferon alpha in patients with advanced
renal cell carcinoma: Clinical and biomarker analysis. Cancer. 2010 Jan 1;116(1):57-65.
54. Soong SJ, Ding S, Coit D, Balch CM, Gershenwald JE, Thompson JF, Gimotty P; AJCC Melanoma Task Force.
Predicting Survival Outcome of Localized Melanoma: An Electronic Prediction Tool Based on the AJCC Melanoma
Database. Ann Surg Oncol. 2010 Aug;17(8):2006-14. Epub 2010 Apr 9.
55. Vadhan-Raj S, Trent J, Patel S, Zhou X, Johnson MM, Araujo D, Ludwig JA, O’Roark S, Gillenwater AM, Bueso-Ramos
C, El-Naggar AK, Benjamin RS. Single-dose Palifermin Prevents Severe Oral Mucositis in Cancer Patients during Multicycle Chemotherapy: A Double-blind, Randomized Trial. Ann Int Med. 2010 Sep 21;153(6):358-67.
56. Ellerhorst JA, Greene VR, Ekmekcioglu S, Warneke CL, Johnson MM, Cooke CP, Wang LE, Prieto VG, Gershenwald
JE, Wei Q, Grimm EA. Clinical Correlates of NRAS and BRAF Mutations in Primary Human Melanoma. Clin Cancer
Res. 2010 Oct 25. [Epub ahead of print]
57. Bedikian AY, Johnson MM, Warneke CL, Papadopoulos NE, Kim KB, Hwu WJ, McIntyre S, Rohlfs M, Homsi J, Hwu
P. Does Complete Response to Systemic Therapy in Patients with Stage IV Melanoma Translate into Long-term Survival?
Melanoma Res. 2010 Nov 22. [Epub ahead of print]
58. Ayala-Ramirez M, Feng L, Johnson MM, Habra MA, Rich T, Busaidy N, Cote GJ, Perrier N, Patel S, Waguespack S,
Jimenez C. Clinical Factors for Metastases and Overall Survival in Patients with Pheochromocytomas and Sympathetic
Paragangliomas: Primary Tumor Size and Primary Tumor Type. J Clin Endocrinol Metab. 2010 Dec 29. [Epub ahead of
print]
59. Thompson JF, Soong SJ, Balch CM, Gershenwald JE, Ding S, Coit DG, Flaherty KT, Gimotty PA, Johnson T, Johnson
MM, Leong SP, Ross MI, Byrd DR, Cascinelli N, Cochran AJ, Eggermont AM, McMasters KM, Mihm MC Jr, Morton
DL, Sondak VK. Prognostic Significance of Mitotic Rate in Localized Primary Cutaneous Melanoma: An Analysis of
Patients in the Multi-Institutional American Joint Committee on Cancer Melanoma Staging Database. J Clin Oncol. 2011
Apr 25. [Epub ahead of print]
60. Berry DA,Ueno NT, Johnson MM, Lei X,Caputo J, Smith DA,Yancey LJ, Crump M, Stadtmauer EA, Biron P, Crown JP,
Schmid P, Lotz JP, Rosti G, Bregni M, Demirer T. High-dose chemotherapy with autologous hematopoietic stem cell
transplantation in metastatic breast cancer: Overview of six randomized trials, J Clin Oncol. 2011 Aug 20;29(24):3224-31.
Epub 2011 Jul 18.
61. Berry DA, Ueno NT, Johnson MM, Lei X, Caputo J, Rodenhuis S, Peters WP, Leonard RC, Bearman SI, Tallman MS,
Bergh J, Nitz UA, Gianni A, Basser RL, Zander AR, Coombes RC, Roché H, Tokuda Y, Schrama JG, Hortobagyi GN,
Bregni M, Demirer T. High-dose chemotherapy with autologous stem cell support as adjuvant therapy in breast cancer:
Overview of 15 randomized trials, J Clin Oncol. 2011 Aug 20;29(24):3214-23. Epub 2011 Jul 18.
62. Kim K, Kim KB, Prieto V, Joseph RW, Diwan AH, Gallick GE, Papadopoulos NE, Bedikian AY, Camacho LH, Hwu P,
Ng CS, Wei W, Johnson MM, Wittemer SM, Vardeleon A, Reckeweg A, Colevas AD. A randomized phase II study of
cilengitide (EMD 121974) in patients with metastatic melanoma. Melanoma Res. 2012 Aug;22(4):294-301. PMID:
22668797 [PubMed - indexed for MEDLINE]
63. Chakravarti N, Peddareddigari VGR, Warneke CL, Johnson MM, Overwijk MW, Hwu P, Prieto VG. Differential
Expression of the G-protein-coupled Formyl Peptide Receptor in Melanoma Associates with Aggressive Phenotype, AmJ
Dermatopathology, Am J Dermatopathol. 2013 Apr;35(2):184-90. PMID: 23147350 [PubMed - indexed for MEDLINE]
64. Bilen MA, Johnson MM, Mathew P, Pagliaro LC, Araujo JC, Aparicio A, Corn PG, Tanir N, Wong F, Fisch MJ,
Logothetis C, Tu SM. Randomized phase 2 study of bone-targeted therapy containing strontium-89 in advanced castrate-
154
sensitive prostate cancer. Cancer. Cancer. 2015 Jan 1;121(1):69-76. doi: 10.1002/cncr.28971. Epub 2014 Aug 22. PMID:
25155428[PubMed - in process]
Abstracts:
1. Barrows LH, Stricklin MD, Siconolfi SF. The Relationship Between Bioelectrical Resistance and Fat-Free Mass Under
Conditions of Different Frequency, Temperature, and Time. [Presented at the Aerospace Medical Association annual
meeting in Cincinnati, OH, May, 1991].
2. Lathers CM, Charles JB, Mukai CN, Riddle JM, Jacobs FO, Bennett BS, Lewis D, Fortney S, Frey MB, Stricklin MD,
Schneider VS. Heart Rate Responses to Lower Body Negative Pressure (LBNP) During Seventeen Weeks of Bedrest.
[Presented at the Federation of American Societies for Experimental Biology annual meeting in Anaheim, CA, April,
1992].
3. Hayes JC, McBrine JJ, Roper ML, Stricklin MD, Siconolfi SF, Greenisen MC. Effects of Space Shuttle Flights on Skeletal
Muscle Performance. [Presented at the Federation of American Societies for Experimental Biology annual meeting in
Anaheim, CA, April, 1992].
4. Yang WT, Whitman GJ, Johnson MM, Bolanos-Clark M, Aldefer J, Kushwaha AC. Needle Localization for Excisional
Biopsy of Breast Lesions: Comparison of Full Field Digital versus Screen-film Mammographic Guidance on Procedural
Time. [Presented at the 88th Annual Meeting of the Radiological Society of North America, December 1-6, 2002].
RADIOLOGICAL SOC, Source: RADIOLOGY Volume: 225 Pages: 417-417 Supplement: Suppl. S Published:
NOV 2002.
5. Pawlik TM, Ross MI, Johnson MM, Bedrosian I, Schacherer CW, Mansfield PF, Lee JE, Cormier JN, Gershenwald, JE.
Predictors and natural history of in-transit melanoma after sentinel lymphadenectomy [Presented at the 57th Annual
Meeting of the Society of Surgical Oncology, New York, NY, March 18-21, 2004]. LIPPINCOTT WILLIAMS &
WILKINS, Source: ANNALS OF SURGICAL ONCOLOGY Volume: 11 Issue: 2 Pages: S61-S61 Supplement:
Suppl. S Published: FEB 2004.
6. Gershenwald JE, Prieto VG, Schacherer CW, Johnson MM, McClain DM, Mansfield PF, Lee JE, Ross MI. The impact of
microscopic tumor burden in sentinel node-positive melanoma patients: Implications for future clinical trial design.
[Presented at the Second International Melanoma Research Congress, Phoenix, AZ, November 13-16, 2004].
7. Gannon CJ, Rousseau Jr DL, Ross MI, Johnson MM, Lee JF, Mansfield PF, Cormier JN, Prieto VG, Gershenwald JE.
Sentinel lymph node biopsy after previous wide local excision accurately reflects the status of the regional nodal basin in
patients with primary melanoma. [Presented at the 4th International Sentinel Node Conference, Los Angeles, CA,
December 3-6, 2004].
8. Aloia T, Gershenwald JE, Ross MI, Lee JE, Johnson MM, Cormier JN, Ng C, Mansfield PF. Utility of CT and MRI
Staging in Patients with Sentinel Lymph Node-Positive Melanoma. [Presented at the 4th International Sentinel Node
Conference, Los Angeles, CA, December 3-6, 2004].
9. Bedikian AY, Johnson MM, Broemeling LD, Papadopoulos NE, Kim KB, Camacho LH, Hwu P. Prognostic Factors
Determining Long Term Survival of Patients with Unresectable Stage III and Stage IV Metastatic Melanoma (MM)
Treated with Combination therapy or IL-2 based Biochemotherapy (BCC). Journal of Clinical Oncology, 2005 ASCO
Annual Meeting Proceedings. Vol 23, No. 16S, Part I of II (June 1 Supplement), 2005: 7544.
10. Prieto VG, Mourad-Zeidan AA, Johnson MM, Diwan AH, Lazar AJ, Shen SS, Reed JA, Bar-Eli M. Analysis of Galectin-3
Expression in Melanocytic Lesions by Tissue Array. Possible Involvement in Tumor Progression. [Presented at the
United States and Canadian Academy of Pathology Annual Meeting, September 2005].
11. Guray M, Sun M, Albarracin CT, Edelweiss M, Johnson MM, Esteva FJ, Yu D, Sahin AA. Significant loss of PTEN
protein expression in lymph node metastases of primary breast cancer: An immunohistochemical study using tissue
microarray. NATURE PUBLISHING GROUP. Source: LABORATORY INVESTIGATION Volume: 86, Pages: 29A29A Supplement: Suppl. 1 Meeting Abstract: 122 Published: JAN 2006.
12. Prieto VG, Diwan AH, Lazar AFJ, Johnson MM, Schacherer C, Gershenwald, JE. Histologic quantification of tumor size
in sentinel lymph node metastases correlates with prognosis in patients with cutaneous malignant melanoma. NATURE
PUBLISHING GROUP. Source: LABORATORY INVESTIGATION Volume: 86 Pages: 87A-87A Supplement: Suppl.
1 Meeting Abstract: 391 Published: JAN 2006.
13. P Mathew, PF Thall, MM Johnson, WK Oh, AA Meluch, MJ Morris, P Troncoso, CD Bucana, IJ Fidler, CJ Logothetis.
Preliminary results of a randomized placebo-controlled double-blind trial of weekly docetaxel combined with imatinib in
men with metastatic androgen-independent prostate cancer (AIPC) and bone metastases (BM). [Presented at the 2006
Annual Meeting of the American Society of Clinical Oncology, Atlanta, GA, June 2-6, 2006]. Source: JOURNAL OF
CLINICAL ONCOLOGY Volume: 24 Issue: 18 Pages: 232S-232S Part: Part 1 Suppl. S Supplement: Part 1 Suppl.
S Published: JUN 20 2006.
14. Moussallem C, Lopez A, Moore S, Gauthier AM, Johnson M, Ibrahim N. Fulvestrant (F) in metastatic breast cancer:
standard dose (Std) vs loading dose (Ld). A retrospective study. [Presented at the 2006 Annual Meeting of the American
Society of Clinical Oncology, Atlanta, GA, June 2-6, 2006]. Journal of Clinical Oncology, 2006 ASCO Annual Meeting
Proceedings Part I. Vol 24, No. 18S (June 20 Supplement), 2006: 10575
15. Andtbacka RH, Gershenwald JE, Prieto VG, Johnson M, Diwan H, Lee JE, Mansfield PF, Schacherer CW, Ross MI.
Microscopic tumor burden in sentinel lymph nodes (SLNs) best predicts nonsentinel lymph node (NSLN) involvement in
155
16.
17.
18.
19.
20.
21.
22.
23.
24.
patients with melanoma. [Presented at the 2006 Annual Meeting of the American Society of Clinical Oncology, Atlanta,
GA, June 2-6, 2006]. AMER SOC CLINICAL ONCOLOGY, Source: JOURNAL OF CLINICAL ONCOLOGY
Volume: 24 Issue: 18 Pages: 454S-454S Part: Part 1 Suppl. S Supplement: Part 1 Suppl. S Published: JUN 20 2006.
Lee JE, Wang Y, Vo Amy, Gershenwald JE, Ross MI, Johnson MM, McClain DM, Jin R. Association of HLA class II
alleles with melanoma incidence. [Presented at the 14th SPORE Investigators’ Workshop, Baltimore, MD, July 2006]
Chun YS, Wang Y, Gershenwald JE, Ross MI, Johnson MM, Liu P, Schacherer CW, Reveille JD, Lee JE. HLA class II
alleles predict recurrence and pattern of failure in early-stage melanoma patients. Abstract ASCO No. 8503. [Presented at
the 2007 Annual Meeting of the American Society of Clinical Oncology, Chicago, IL, June 4-8, 2007]. [Journal of Clinical
Oncology, 2007 ASCO Annual Meeting Proceedings Part I. Vol 25, No. 18S (June 20 Supplement), 2007: 8503].
Kim KB, Diwan AH, Papadopoulos NE, Bedikian AY, Camacho LH, Hwu P, Johnson MM, Colevas DA, Prieto VG.A
Randomized Phase II Study of Cilengitide (EMD 121974) in Patients with Metastatic Melanoma. American Society for
Clinical Oncology, January 2007 [Journal of Clinical Oncology, 2007 ASCO Annual Meeting Proceedings Part I. Vol 25,
No. 18S (June 20 Supplement), 2007: 8548].
Berry DA, Ueno NT, Johnson MM, Lei X, Lopez V, Caputo J, Yancey LJ, Bregni M, Demirer T. High-dose
chemotherapy with autologous stem-cell support versus standard-dose chemotherapy: meta-analysis of individual patient
data from 15 randomized adjuvant breast cancer trials. [Presented at the 2007 meeting of the San Antonio Breast Cancer
Symposium.] SPRINGER, Source: BREAST CANCER RESEARCH AND TREATMENT Volume: 106 Pages: S5S5 Supplement: Suppl.1 Published: DEC 2007.
Gershenwald J, Thompson J , Warneke C, Ross M, Johnson M, McMasters K, Delman MK, Sabe l M, Noyes D, Kraybill
W, Coit D, Leong S, Eggermont A. (Re)-Defining Indications For Sentinel Lymph Node Biopsy (SLNB) in Patients (Pts)
With Thin Melanoma - Preliminary Results of an International Thin Melanoma Working Group. [Presented at the 2007
meeting of the International Sentinel Node Society, Sydney, Australia, February 18-20, 2008.] SPRINGER, Source:
ANNALS OF SURGICAL ONCOLOGY Volume: 15 Pages: 4-4 Supplement: Suppl. 1 Published: FEB 2008.
Wang Y, Kesmodel SB, Vo AH, Liu H, Chun YS, Gershenwald JE, Cormier JN, Ross MI, Wang DY, McClain DM,
Schacherer CW, Henderson L, Liu P, Johnson MM, Berry DA, Reveille JD, Lee JE. Association of the TGF-Beta1 codon
10 T polymorphism with improved outcomes in early-stage melanoma patients. [Presented at the 2008 annual meeting of
the American Association of Cancer Research, San Diego, CA, April 12-16, 2008]. [AACR Meeting Abstracts, Apr 2008;
2008: 4690].
Kebriaei P, Jones D, Johnson MM, Gutierrez K, Giralt S,de Lima M, Korbling M, Khouri IF, Popat U, Qazilbash MH,
Alousi A, Ciurea S, Cooper L, Shpall E, Champlin R.Addition of Umbilical Cord Blood (UCB) Unit to Reduced Intensity
Conditioning (RIC) Regimen to Augment Graft Versus Tumor (GVT) in Patients (pts) with Advanced Hematologic
Malignancies. [Presented at the 2009 annual meeting of the International Umbilical Cord Blood Transplantation
Symposium, Los Angeles, CA, June 5-6, 2009].
Caudle A, Ross MI, Prieto VG, Warneke CL, Lee JE, Johnson MM, Gardner, Royal, Cormier, Lucci, Gershenwald JE.
Mitotic Rate Predicts Sentinel Lymph Node Involvement in Cutaneous Melanoma: Impact of the 7th Edition AJCC
Melanoma Staging System, [Presented at the 2010 annual meeting of the Society of Surgical Oncology, St. Louis,
Missouri, March 3-7, 2010].
Chakravarti N, Peddareddigari VGR, Warneke CL, Johnson MM, Hwu P, Prieto VG. Increased expression of formyl
peptide receptor (FPR) and formyl peptide receptor like-1 (FPRL1) correlates with high-risk clinical/histologic features in
melanoma. [Presented at the 2011 annual meeting of the American Association for Cancer Research, Orlando, Florida,
April 2 – 6, 2011].
Book Chapters:
1. AJCC Cancer Staging Manual: 7th Edition (2010) Edge SB, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A (Eds).
Springer, New York, New York. (Melanoma Staging Chapter)
Letters to the Editor:
1. Choi H, Johnson MM. Reply. Am J Roentgenol. 2005 Nov; 185(5):1366-7.
Other - Posters:
1. Barrows LH, Stricklin MD, Wong WW, Klein PD, Inners, LD, Siconolfi SF. Comparison of Total Body Water Estimates
from 18O and Bioelectrical Response Prediction Equations. [Poster presented at the Federation of American Societies for
Experimental Biology annual meeting in Anaheim, CA, April, 1992].
2. Bell M, Stricklin MD. A Macro to Facilitate the Visualization of Individual Patient Efficacy and Safety During an
Investigational (Phase III) Clinical Trial. [Poster presented at the SAS® Users Group International annual meeting in
Dallas, TX, April, 1994].
3. Stricklin, MD. An Ophthalmic Clinical Trial with a Group Sequential Design and Multiple Comparisons. [Poster
presented at the Society for Clinical Trials annual meeting in Houston, TX, May, 1994].
4. Bell M, Stricklin MD, Munsell, MF. Electronic Documentation for Validation of Statistical Analysis Programming for
Data from Clinical Trials. [Poster presented at the Society for Clinical Trials annual meeting in Seattle, WA, May, 1995].
5. Moore, MD, Herson J, Gonen M. Analysis of Clinical Events Using Linearized Rates. [Poster presented at the American
156
Statistical Association annual meeting in Dallas, TX, August, 1998].
6. Gayed I, Sureshbabu W, Iyer R, Macapinlac H, Johnson M, Podoloff DA. Positron Emission Tomography Versus
Computerized Tomography for the Identification of Melanoma Metastases. [Poster presented at the 49th Annual Meeting
of the Society of Nuclear Medicine, June 15-19, 2002]. SOC NUCLEAR MEDICINE, Source: JOURNAL OF
NUCLEAR MEDICINE Volume: 43 Issue: 5 Pages: 294P-294P Supplement: Suppl. S Meeting Abstract: 1187 Published:
MAY 2002.
7. Gayed IW, Vu TT, Macapinlac HA, Johnson MM, Delpassand ES, Wong F, Kim E, Podoloff DA. Comparison of Bone
and F-18 FDG Scans in the Evaluation of Bony Metastases. [Poster presented at the 49th Annual Meeting of the Society
of Nuclear Medicine, June 15-19, 2002].
8. Gayed I, Boccalandero F, Sdringola S, Johnson M, Butler C, Gee-Johnson S, Swafford I. Comparison of Resting
Echocardiography and Gated SPECT in the Evaluation of Wall Motion Abnormalities. [Poster presented at the 7th
Annual Meeting of the American Society of Nuclear Cardiology, September 26-29, 2002].
9. Wang XS, Johnson MM, Broemeling LD, Janjan N, Komaki R, Mendoza T, Cleeland CS. Longitudinal Model for CancerRelated Symptoms During Radiotherapy Among Patients with Gastrointestinal and Lung Cancer. [Poster presented at the
Annual Meeting of the International Society for Quality of Life Research, October 30 - November 2, 2002].
10. Vadhan-Raj S, Skibber JM, Crane C, Bueso-Ramos CE, Rodriquez-Bigas MA, Feig BW, Lin EH, Ajani JA, Collard M,
Johnson MM, Hamilton SR, JanJan N. Randomized, Double-Blind, Placebo-Controlled Trial of Epoetin Alfa (Procrit) in
Patients with Rectal and Gastric Cancer Undergoing Chemo-Radiotherapy (CT/RT) Followed by Surgery: Early
Termination of the Trial Due to Increase Incidence of Thromboembolic Events (TEE). Poster presented at the American
Society of Hematology 46th Annual Meeting, San Diego, CA, December 4-7, 2004]. AMER SOC HEMATOLOGY,
Source: BLOOD Volume: 104 Issue: 11 Pages: 797A-797A Part: Part 1 Meeting Abstract: 2915 Published: NOV 16 2004.
11. Pawlik TM, Ross MI, Johnson MM, Prieto VG, Schacherer CW, McClain DM, Mansfield PF, Lee JE, Cormier JN,
Gershenwald JE. Sentinel lymph node biopsy for primary cutaneous desmoplastic melanoma: Is there a role? [Poster
presented at the 4th International Sentinel Node Conference, Los Angeles, CA, December 3-6, 2004].
12. Sun X, Wang E, Jones DM, Shen H, Johnson MM, Issa JP, Amin H, Ginsberg CF, Kantarjian HM, Andreeff M,
Kornblau SM, Glassman AB, Arlinghaus RB. SOX4 Gene Expression in Human Leukemia. [Poster presented at the
American Association for Cancer Research Annual Meeting, Washington, D.C., April 1- 5, 2006].
13. Hoff AO, Toth BB, Altundag K, Guarneri V, Adamus A, Nooka AK, Sayegh GG, Johnson MM, Gagel RF, Hortobagyi
GN. Osteonecrosis of the Jaw in Patients Receiving Intravenous Bisphosphonate Therapy. [Poster presented at the 2006
Annual Meeting of the American Society of Clinical Oncology, Atlanta, GA, June 2-6, 2006]. Source: JOURNAL OF
CLINICAL ONCOLOGY Volume: 24 Issue: 18 Pages: 475S-475S Part: Part 1 Suppl. S Supplement: Part 1
Suppl. S Meeting Abstract: 8528 Published: JUN 20 2006.
14. Gershenwald JE, Morton DL, Thompson JF, Kirkwood JM, Soong S, Balch CM, Eggermont AM, Sondak VK, Johnson
MM, Warneke C, Collaborators of the AJCC/UICC Melanoma Task Force. Staging and prognostic factors for stage IV
melanoma: Initial results of an American Joint Committee on Cancer (AJCC) international evidence-based assessment of
4895 melanoma patients. Poster presented at the 44th Annual Meeting of the American Society of Clinical Oncology, May
2008 [J Clin Oncol 26: 2008 (May 20 suppl; abstr 9035)].
15. Ekmekcioglu S, Johnson MM, Gershenwald JE, Prieto VG, Grimm EA. iNOS Expression in Tumor Cells and Tumor
Associated Macrophages in Melanoma. [Poster presented at Chemical and Biological Aspects of Inflammation and
Cancer, October 14-17, 2008.
16. Albarracin CT, Sigauke E, Whitman G, Yang WT, Resetkova E, Johnson MM, Nguyen CV, Sneige N. Atypical and
Columnar Cell Lesions in Breast Needle Biopsies for Indeterminate Microcalcifications: Predictors of Higher Risk
Findings Requiring Surgical Excision. [Poster presented at the 2008 meeting of the San Antonio Breast Cancer
Symposium.] AMER ASSOC CANCER RESEARCH, Volume: 69 Issue: 2 Pages: 206S-206S Supplement: Suppl.
S Published: JAN 15 2009.
17. Berry DA, Ueno NT, Johnson MM, Lei X, Smith DA, Caputo J, Yancey LJ, Bregni M, Demirer T. High-dose
chemotherapy with autologous stem-cell support versus standard-dose chemotherapy: meta-analysis of individual patient
data from 6 randomized metastatic breast cancer trials. [Poster presented at the 2008 meeting of the San Antonio Breast
Cancer Symposium.] AMER ASSOC CANCER RESEARCH, Source: CANCER RESEARCH Volume: 69 Issue:
2 Pages: 381S-381S Supplement: Suppl. S Published: JAN 15 2009.
18. Atkins MB, Long GV, Warneke CL, Carlino MS, DeRose E, Johnson MM, Brown PT, Lee MY, Kefford RF, Gershenwald
JE. Unraveling the Prognostic Heterogeneity in Patients with Advanced Melanoma Between Australia and the United
States: Preliminary Report of the PHAMOUS Study. Poster presented at American Society Clinical Oncology Annual
Meeting, June 2010 [J Clin Oncol 28:15s, 2010 (suppl; abstr 8516)].
19. Carlino MS, Atkins MB, Warneke CL, Long GV, DeRose ER, Johnson MM, Brown PT, Lee MY, Gardner J, Hamilton
A, Alvarado G, Kefford R, Gershenwald JE. Differences between Australia (OZ) and the United States (US) in the
patterns, prognosis, and treatment of melanoma CNS metastases: analysis from the PHAMOUS (prognostic
heterogeneity in patients with advanced melanoma between OZ and the US) study. Poster presented at Society for
Melanoma Research, 7th International Melanoma Congress, Sydney, Australia, November 2010.
20. Long GV, Atkins MB, Warneke CL, Carlino MS, DeRose E, Johnson MM, Brown PT, Roberson F, Gardner J, Alvarado
G, Lee MY, Kefford RF, Gershenwald JE.. Unraveling the Prognostic Heterogeneity in Patients with Advanced
157
21.
22.
23.
24.
Melanoma (MM) Between Australia (OZ) and the United States (US): The PHAMOUS STUDY. Poster presented at
Society for Melanoma Research, 7th International Melanoma Congress, Sydney, Australia, November 2010.
Vadhan-Raj S, Hagemeister F, Fayad LE, Zhou X, O’Roark SS, Ames K, Rodriguez MA, Fanale MA, Pro B, MM
Johnson, McLaughlin P, Bueso-Ramos CE, Younes A, Kwak L, Romaguera JE. Randomized, double-blind, placebocontrolled, dose and schedule-finding study of AMG 531 in chemotherapy-induced thrombocytopenia (CIT): Results of a
phase I/II study. Poster presented at 2010 ASH Annual Meeting, Blood (ASH Annual Meeting Abstracts) 2010 116:
Abstract 1544).
Chakravarti N, Ivan D, Ross MI, Ilagan JL, Warneke CL, Kim K, Papadopoulos NE, Cain S, Gershenwald JE, Johnson MM, Bedikian
AY, Royal RE, Cormier JN, Hanna EY, Lee JE, Prieto VG, en Hwu WJ. Biomarker study in patients with resectable AJCC stage
IIIc or stage IV (M1a) melanoma treated in a randomized phase II neoadjuvant trial. Poster presented at 2013 American
Society Clinical Oncology Annual Meeting (abstract 9047).
Ky B, Warneke CL, Lenihan D, Cheema PS, Moore DF, Campbell MG, C Yeshwant, Adams PT, Krone R, Carver JR,
Nasta S, Svoboda J, Schuster S, Reddy N, Patel S, Rieber A, Johnson M, Fisch MJ. Clinical Risk Prediction in
Anthracycline Cardiotoxicity. Poster presented at the 2014 American Society of Clinical Oncology Annual Meeting
(abstract 9624).
Stevens PL, Lenihan DJ, Ky B, Warneke CL, Johnson MM, Abramson VG, Mayer IA, Adams PT, Campbell MG,
Cheema PS, Moore DF, Yeshwant C, Carver JR, Fisch M Prediction and early detection of anthracycline-related cardiotoxicity using
cardiac biomarkers. Poster presented at the 2014 American Society of Clinical Oncology Annual Meeting (abstract 9644).
TEACHING:
Training Programs:
- Introduction to Statistics. Presented through the MD Anderson Office of Protocol Research – Quality Assurance as part
of their orientation program, “Clinical Research Training - History of Research and IRB, Informed Consent Process &
Documents & Introduction to Statistics.” October 2002; January 2003; February 2003; February 2004; May 2004; June
2004; July 2004; June 2005, August 2007
- Data Analysis: Summarizing and Presenting Data. Presented through the MD Anderson Office of Trainee Support
Services as part of their Core Curriculum program. March 2002; April 2004; March 2005; July 2005, July 2006
- Statistics in Clinical Trials. Presented through the MD Anderson Office of Research Education and Regulatory
Management. April 2009
PROFESSIONAL MEMBERSHIP/ACTIVITIES:
Local/State:
- Houston Area Chapter of the American Statistical Association, Member
- National and International:
- American Statistical Association, Member
- International Biometric Society, Member
158
MICHAEL H. KUTNER
Rollins Professor
Department of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health
1518 Clifton Road, NE Atlanta, Georgia 30322
Voice: 404-712-9708 Email: [email protected]
EDUCATION
Ph.D. 1971
Texas A & M University, College Station, Texas, in statistics.
Doctoral research in the area of variance component estimation.
M.S. 1962
Virginia Polytechnic Institute and State University, Blacksburg, Virginia, in statistics.
B.S. 1960
Central Connecticut State College, New Britain, Connecticut, in mathematics.
PROFESSIONAL EMPLOYMENT
• 2009 - Present Rollins Professor, Department of Biostatistics and Bioinformatics, Emory University,
Rollins School of Public Health, Atlanta, Georgia.
• 2004 - 2009
Rollins Professor and Chair, Department of Biostatistics and Bioinformatics, Emory University,
Rollins School of Public Health, Atlanta, Georgia.
• 2002 - 2003
Interim Chair, Department of Biostatistics, Emory University, Rollins School of Public
• Health, Atlanta, Georgia.
• 2001 - Present Director, Biostatistics Consulting Center, Department of Biostatistics, Emory University,
Rollins School of Public Health, Atlanta, Georgia.
Research Professor, Department of Biostatistics, Emory University, Rollins School of
• 2000 - 2003
• Public Health, Atlanta, Georgia.
• 1994 - 1999
Chairman, Department of Biostatistics and Epidemiology, The Cleveland Clinic
• Foundation, Cleveland, Ohio.
• 1991 - 1993
Professor, Division of Biostatistics and Associate Dean for Academic Affairs, School of Public
Health, Emory University, Atlanta, Georgia.
• 1990 - 1991
Director, Division of Biostatistics and Associate Dean for Academic Affairs, School of Public
Health, Emory University, Atlanta, Georgia.
• 1988 - 1990
Professor and Director, Division of Biostatistics, Department of Epidemiology and
• Biostatistics, Emory University, Atlanta, Georgia.
• 1986 - 1988
Professor and Acting Chairman, Department of Statistics and Biometry, Emory
• University, Atlanta, Georgia.
• 1981 - 1985
Professor of Statistics and Biometry, Emory University, Atlanta, Georgia.
• 1975 - 1980
Associate Professor of Statistics and Biometry, Emory University, Atlanta, Georgia.
• 1971 - 1975
Assistant Professor of Statistics and Biometry, Emory University, Atlanta, Georgia.
• 1970 - 1971
Assistant Professor Statistics, Institute of Statistics, Texas A & M University; teaching graduate
statistics and research connected with dissertation.
• 1962 - 1967
Assistant Professor of Mathematics, College of William & Mary, Williamsburg, Virginia; teaching
senior-graduate statistics and numerical analysis, differential equations, calculus.
• 1964 - 1965
Dow-Badishe Chemical Company, Williamsburg, Virginia; consulting and teaching experimental
design and analysis.
• 1963 - 1967
NASA, Langley Air Force Base, Newport News, Virginia; part-time teaching and
consulting.
PROFESSIONAL AWARDS/HONORS
• 2012 – Cited as one of Texas A&M’s most distinguished alumni in book entitled, Strength in Numbers: The
Rising of Academic Statistics Departments in the U.S., Springer, Edited by Alan Agresti & Xiao-Li Meng
• October 2012 – Mike Kutner Junior Faculty Poster Session named in my honor, Southern Regional Council on
Statistics, Summer Research Conference
• August 2011 – Recipient of the Wilfred J. Dixon Award for Excellence in Statistical Consulting, American
Statistical Association,
• March 2011 – Recipient of the Charles R. Hatcher, Jr., M.D., Award for Excellence in Public Health, Woodruff
Health Sciences Center
• November 2010 – Invited delegate of the People to People “Statistical Science Delegation” that visited China
under the leadership of the President and Executive Director of the American Statistical Association. Visited
Beijing (Renmin University and National Bureau of Statistics), Xi’an (Xi’an University of Finance and
Economics and Northwest University) and Shanghai (East China Normal University and Fudan University).
159
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
The purpose of the trip was to explore possible faculty and student exchange programs between our two
countries. The Biostatistics Department has recruited doctoral students from both Renmin and Fudan
University.
November 2009 – Inducted as member of ASPH/Pfizer Public Health Academy of Distinguished Teachers
2009 – Recipient of Mu Sigma Rho National Statistical Honor Society Statistical Education Award for lifetime
devotion to the discipline of teaching statistics
May 2008 – Recipient of the Thomas F. Sellers, Jr. Award for exemplifying the ideals of public health and
serving as a role model and mentor to his colleagues
2008 – Appointed to External Advisory Committee by the Department of Statistics, Texas A&M University
2008-2009 – Inducted as President of the Southern Regional Council on Statistics (SRCOS)
2008-2013 – Appointed Member of the Clinical Research Advisory Committee of the Shriner’s Hospitals
August 2006 – Recipient of Georgia Chapter, ASA, distinguished service award
October 2006 – Elected President-Elect, SRCOS (2007-2008)
March 2004 – Named Endowed Rollins Professor and Chair of Biostatistics
September 2002 – Recipient of the 2002 Southern Region Council on Statistics (SRCOS) Paul Minton
Award for distinguished service to the statistical profession
September 1999 – Elected member of International Statistical Institute
June 1997 – Excellence in Research Award co-authorship on “Reducing Frailty and Falls in Older Persons: An
Investigation of Tai Chi and Computerized Balance Training.” Journal of American Geriatric Society, 44:489497, 1996. Selected as the best paper of the decade.
May 1997 – Inducted into inaugural class of the “Academy of Distinguished Graduates,” College of Science,
Texas A&M University
Aug 6, 1996 – Recipient of the Founders Award, American Statistical Association.
Dec 2, 1995 – Certificate of Appreciation in recognition of dedicated service to the American Statistical
Association as member of the Board of Directors, 1993-1995.
Aug 14, 1995 – Best Invited Paper, Section on Teaching of Statistics in the Health Sciences, 1995 Joint Statistical
Meetings, Orlando, Florida. (with Ralph O'Brien.)
July 1995 – NSF funded participant Academe/Industry Collaboration Project, Cal Poly, San Luis Obispo,
California.
1990-1991 – Inaugural President, NIH/GCRC Statisticians Group
September 1991 – Recipient of Chapter Service Recognition Award, Atlanta Chapter, American Statistical
Association.
August 1984 – Elected Fellow of the American Statistical Association.
1984 – Recipient of H. O. Hartley Award, Texas A&M University
Summer 1973 – NSF funded participant Regional Conference on Multivariate Statistical Analysis, Tuscaloosa,
Alabama.
1969-1970 – NIH Trainee Fellowship, Texas A&M University
1969 – Graduate Research and Teaching Assistant, Texas A&M University.
1967-1968 – NSF Faculty Fellowship.
1962 – Elected Pi Mu Epsilon (Honorary Math Society).
1960-1962 – Teaching Assistantship, Virginia Polytechnic Institute and State University.
EMORY PHILANTHROPIC GIFTS
• Donated 1994 Atlanta Olympic Street banner to the Dobbs University Center
• Established the Michael H. Kutner Alumnus Award given annually to recognize a former department graduate
student for Distinguished Service to the Field
• Established the Michael H. Kutner Outstanding Graduate Student Award given annually to a doctoral student in
the Department of Biostatistics and Bioinformatics
• Donated to the Department of Biostatistics and Bioinformatics paintings, artwork and potted plants for the entire
3rd floor and a portion of the 2nd floor
• Donated all of the wine for the Department’s 50th Anniversary Celebration on October 17, 2014
• Donated funds to support the development of an Emory Faculty Club
BOOKS
1. Michael H. Kutner, Christopher J. Nachtsheim and John Neter, Applied Linear Regression Models, 4th
edition, McGraw-Hill/Richard D. Irwin, Inc., Chicago, Illinois, 2004. (under revision)
2. Michael H. Kutner, Christopher J. Nachtsheim, John Neter and William Li, Applied Linear Statistical Models,
5th edition, McGraw-Hill/ Richard D. Irwin, Inc., Chicago, Illinois, 2005. (under revision)
160
3. Christopher J. Nachtsheim and Michael H. Kutner, Introduction to Business Statistics, (under preparation)
BOOK CHAPTERS, PROCEEDINGS AND TECHNICAL REPORTS
Book Chapters:
1. Nixon DW, Moffitt SD, Olkowski Z, Ansley J, Kutner MH, Lawson DH, Heymsfield SB, Lynn MJ and
Rudman D. “Parenteral, Nutritional Supplementation in Recent Advances in Clinical Nutrition, Volume 1.
Howard, Alan and Baird, Ian McLean (eds). John Libbey and Company, Ltd, Londonm 1981.
2. Nixon DW, Lawson DH, Kutner MH, Moffitt SD, Ansley J, Heymsfield SB, Lynn MJ, Wesley M, Yancey
R and Rudman D. “Effect of Total Parenteral Nutrition on Survival in Advanced Colon Cancer.” Cancer Detection
and Prevention. HE Nieburgs (ed). Marcel Dekker, Inc, New York, 1982.
3. Waring GO III, Refractive Keratotomy for Myopia and Astigmatism, Mosby Year Book 1992; Chapter 13: Lynn
MJ, Waring GO III and Kutner MH, “Predictability of Refractive Keratotomy,” pp. 341-380. Chapter 22: Nizam
A, Lynn MJ, Kutner MH and Waring GO III, “Bilateral Results of Radial Keratotomy,” pp. 849-862. Chapter 24:
Waring GO III, Lynn MJ and Kutner MH, “Stability of Refraction after Refractive Keratotomy,” pp. 937-968.
4. Peck R, Haugh LD and Goodman A. Statistical Case Studies: A Collaboration Between Academe and Industry.
Society for Industrial and Applied Mathematics, 1998; Chapter 16: Kutner MH, Easley KA, Jones SC and
Bryce GR, “Cerebral Blood Flow Cycling: Anesthesia and Arterial Blood Pressure,” pp. 203-216.
Proceedings:
1. Kutner MH, Brown AC and Miller K. “A Critique: Hair Sulfur Analysis for Evaluation of Normal and
Abnormal Hair.” Proceedings of First Human Hair Symposium, 1974.
2. Tan M, Xiong X and Kutner MH. “Sequential Conditional Probability Ratio Test, Reverse Stochastic
Curtailing and Stochastic Curtailing.” ASA Biopharmaceutical Section Proceedings, 1996.
Technical Reports:
1. Kutner MH. "Maximum Likelihood Analysis of Balanced Incomplete Block Models." Technical Report #7,
NASA (July 1971).
DISSERTATIONS DIRECTED
• 1981, Raymond P. Bain, “Comparison of the Multivariate Analysis of Variance and the Univariate Analysis of
Variance for the Group by Time Repeated Measures Design.”
• 1979, Gamil H. Absood, “Distributions of Functions of Gaussian Random Variables with Applications to
Structural Regression Models.”
• 1977, Jesse Meneses, “On Univariate and Multivariate Statistical Analyses of Repeated Measures and Applications
to a Maintenance Study of Heroin Addicts.”
• 1976, Robert Mosteller, “Regional Discriminant Analysis: Assessment of Breast Cancer Risk.”
• 1974, Brent Blumenstein, “Maximum Likelihood Estimation of Linear Path Regression Models.”
• 1972, Edward L. Frome, “Nonlinear Regression and Spectral Estimation in Biomedical Data Analysis.”
• 1972, Guy C. Davis, Jr., “The Use of Mathematical Models in the Analysis of Indicator-Dilution Curves.”
MASTERS THESIS DIRECTED
1975 Russell Roegner, “Some Statistical Considerations of Venereal Disease Morbidity.”
COURSES TAUGHT AT EMORY
• Linear Models (Graybill); Design and Analysis of Experiments (Winer); Multivariate Methods (Morrison);
Introduction to Theoretical Statistics I & II (Mood, Graybill & Boes); Introduction to Probability (Parzen); Analysis
of Variance and Regression (Neter, Wasserman & Kutner); Statistical Methods (Snedecor and Cochran); Biostatistics
for Medical Students (Colton); Logistic Regression and Survival Analysis (Collett); Experimental Design and Analysis
for the Biological Sciences (Altman); Introduction to Biostatistics (Freedman, et al); Biostatistical Consulting (Derr);
Clinical Trials (Friedman, Furberg & DeMets).
• 2011: Developed & taught BIOS 560R: Basic Fundamentals for Conducting a Clinical Trial, 12 students; Course
Evaluation: 4.3/5 for Course: 4.4/5 for the Instructor
COMMITTEE MEMBERSHIPS/ACTIVITIES
• 2013, Served as Co-Master of Ceremonies, Dinner Banquet, 50th Anniversary Celebration, Texas A&M
Department of Statistics, May 17th.
• 2012, Appointed as Co-Chair for Planning, 50th Anniversary Celebration, Texas A&M, Department of Statistics
• 2011, Member, Selection Committee for Mu Sigma Rho Excellence in Teaching Award
161
Emory University
2013 - 2014
Chair Planning Committee in the department to celebrate the 50th anniversary conference
Oct 17-18, 2014.
2011
Chair, Search Committee, WCI Biostatistics Shared Resource
2011- 2015
Member and Chair, Emory Faculty Life Course Committee
2009
Charter Committee Member, Center for Health in Aging
2006 - 2009
Executive Committee, Computational & Life Sciences Initiative
2006 – 2009
Chair, Brogan Lecture Committee
2006 – 2009
Director, Biostatistics, Epidemiology and Research Design Program, ACTSI
2006 – 2009
Member, ACTSI Executive Committee
2006 – 2007
Chair, Search Committee, EOH Chair
2004 – 2009
Member, WHSC Research Advisory Committee
2004
Organized, planned and raised funds for the dinner celebration of the retirement for Dr. Donna Brogan,
October 22, 2004.
2004
Organized, planned and raised funds for the 40th Anniversary celebration of the Department of
Biostatistics, October 22, 2004. Luncheon speakers: President Jim Wagner, Dean Jim Curran and
Dr. Fadlo Khuri.
2004
Established the Donna J. Brogan Lecture series in the Department of Biostatistics.
2003 – 2005
Chair, Search Committee, Department of Biostatistics Faculty Search
2002 – 2009
Member, Chairs Council, Rollins School of Public Health
2002 – 2004
Chair, Strategic Planning Committee for Biostatistics Consulting Center Initiative
2002 – 2008
Clinical Trials Office Advisory Committee
2000 – 2006
Center for Health in Aging Advisory Board
2000 – 2001
Search Committee, Associate Faculty Recruitment
1992 – 1993
Chair, Curriculum Committee for MPH Program
1992 – 1993
Chair, Appointment, Promotions and Tenure Committee, SPH
1991 – 1993
University Accreditation Committee, SPH Representative
1990 – 1993
Member, Steering Committee, Lovastatin Restenosis Trial
1989 – 1992
Member, Academic Computing Advisory Committee
1991 – 1993
Chairman, Woodruff Fellowship Committee, School of Public Health
1990 – 1993
Member, Executive Committee, SPH
1990 – 1992
Chairman, Admissions Committee, Division of Biostatistics
1990 – 1992
Member, Council of Division Directors, SPH
1974 – 1993
Ex-officio Member, Advisory Committee, Clinical Research Center
1974 – 1993
Chief Biostatistician, Emory General Clinical Research Center (GCRC)
1989 – 1990
NIH/GCRC Statisticians Group Development Team Member
1986 – 1990
Chairman, Medical School Workstations Committee
1983 – 1986
Member, Ad hoc Promotions Committee
1980 – 1981
Member, Task Force: Curriculum Study and Revision
1976 - 1979/
1981 – 1986
Elected Member Executive Committee of Graduate School
1972 – 1976
Member Medical School Study Group
1971 – 1983
Doctoral Written Exam Committee, Chair
The Cleveland Clinic Foundation
Department of Biostatistics and Epidemiology
1994 – 1999
Management Advisory Committee, Chair
1994 – 1999
Space Committee, Chair
1994 – 1999
Member, Operations Group
1994 – 1995
Strategic Planning Task Force, Chair
1994 – 1999
Search Committee, Chair
1994 – 1995
Member, Committee to Review Chargeback System of Department
Research Institute
1994 – 1996
Member, Research Division Committee
1994 – 1996
Case Western Reserve University/Cleveland Clinic Foundation Working Group Member
1994 – 1999
Institutional Review Board consultant
162
PUBLISHED PAPERS
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
Frome EL, Kutner MH and Beuchamp JJ. “Regression Analysis of Poisson Distributed Data.” Journal
of the American Statistical Association, 68:935-940, 1973.
Kutner MH. “Hypothesis Testing in Linear Models (Eisenhart Model 1).” The American Statistician,
28(3):98-100, 1974.
Kutner MH. “Hypothesis Tests in Linear Models.” The American Statistician, 29(3):133-134, 1975.
Hocking RR and Kutner MH. “Some Analytical and Numerical Comparisons of Estimators for the Mixed
A.O.V. Model.” Biometrics, 3(1):19-27, 1975.
Michael RP, Bonsall RW and Kutner MH. “Volatile Fatty Acids, ‘Copulins,’ in Human Vaginal
Secretions.” Psychoneuroendocrinology, 1:153-163, 1975.
Gerron GG, Ansley JD, Isaacs JE, Kutner, MH and Rudman D. “Technical Pitfalls in Measurement of
Venous Plasma NH3 Concentration.” Clinical Chemistry, 22:663-666, 1976.
Davis G and Kutner MH. “The Lagged Normal Family of Probability Density Functions Applied to
Indicator-Dilution Curves.” Biometrics, 32(3):669-675, 1976.
Rudman D, Fleischer AS and Kutner MH. “Concentration of 3', 5' Cyclic Adenosine Monophosphate in
Ventricular Cerebrospinal Fluid of Patients with Prolonged Coma After Head Trauma or Intracranial
Hemorrhage.” New England Journal of Medicine, 295(12):635- 638, 1976.
Wolf SL, Nahai F, Brown DM, Jordan N and Kutner MH. “Objective Determinations of Sensibility in
the Upper Extremity. I: Median Nerve Sensory Conductive Velocities; II: Application of Cutaneous Stimuli in
Control Subjects; III: Application of Cutaneous Stimuli in Patients with Peripheral Nerve Lesions.” Physical
Therapy. 57:1121-1137, 1977.
Sung YF, Kutner MH, Cerine FC and Frederickson EL. “Comparisons of the Effects of Acupuncture
and Codeine on Postoperative Dental Pain.” Anesthesia and Analgesia, 56:473-478, 1977.
Rudman D, Fleischer AS, Kutner MH and Raggio JF. “Suprahypophyseal Hypogonadism and
Hypothyroidism During Prolonged Coma After Head Trauma.” Journal of Clinical Endocrinology and
Metabolism, 45:747-754, 1977.
Kaplan JA, Cannerella C, Jones EL, Kutner MH, Hatcher CR and Dunbar RW. “Autologous Blood
Transfusion During Cardiac Surgery.” The Journal of Thoracic and Cardiovascular Surgery, 74:4-10, 1977.
Rudman D, Kutner MH, Fleming GA, Harris RC, Kennedy EE, Bethel RA and Priest JH. “Effect of 10
Day Courses of Human Growth Hormone on Height of Short Children.” Journal of Clinical Endocrinology
and Metabolism, 46:28-35, 1978.
Ansley JD, Isaacs JW, Rikkers LF, Kutner MH, Nordinger BM and Rudman D. “Quantitative
Tests of Nitrogen Metabolism in Cirrhosis: Relation to Other Manifestations of Liver Disease.”
Gastroenterology, 75(4):570-579, 1978.
Rudman D, Davis GT, Priest JH, Patterson JH, Kutner MH, Heymsfield SB and Bethel RA. “Prevalence of
Growth Hormone Deficiency in Children with Cleft Lip or Palate.” Journal of Pediatrics, 93(3):378-382, 1978.
Rudman D and Kutner MH. “Melanotropic Peptides Increase Permeability of Plasma/ Cerebrospinal
Fluid Barrier.”American Journal of Physiology, 234(3):327-332, 1978.
Wolf SL, Gersh MR and Kutner MH. “Relationship of Selected Clinical Variables to Current Delivered
During Transcutaneous Electrical Nerve Stimulation.” Physical Therapy, 58(12):1478-1485, 1978.
Rikkers LF, Rudman D, Galambos JT, Millikan WJ, Kutner MH, Smith RB, Salam AA, Sones PJ and
Warren D. “A Randomized, Controlled Trial of the Distal Splenorenal Shunt.” Annals of Surgery,
188(3):271-282, 1978.
Kutner NG and Kutner MH. “Race and Sex as Variables Affecting Reaction to Disability.” Archives of
Physical Medicine and Rehabilitation, 60:62-66, 1979.
Rudman D, Kutner MH, Blackston RD, Jansen RD and Patterson JH. “Normal Variant Short Stature:
Subclassification Based on Responses to Exogenous Human Growth Hormone.” Journal of Clinical
Endocrinology and Metabolism, 49:92-99, 1979.
Nixon DW, Murphy GF, Sewell GW, Kutner MH and Lynn MH. “Relationship Between Survival and
Histologic Type in Small Cell Anaplastic Carcinoma of the Lung.” Cancer, 44:1045-1049, 1979.
Heymsfield SB, Fulenwider JT, Nordlinger BM, Barlow R, Sones PJ and Kutner MH. “Accurate
Measurement of Liver, Kidney, and Spleen Volume and Mass by Computerized Axial Tomography.” Annals
of Internal Medicine, 90:185-187, 1979.
Rudman D, Kutner MH, Goldsmith MA and Blackston RD. “Predicting the Response of Growth
Hormone-Deficient Children to Long Term Treatment with Human Growth Hormone.” Journal of Clinical
163
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
Endocrinology and Metabolism 48:472-477, 1979.
Faraj BA, Fulenwider JT, Rypins EB, Nordlinger BM, Ivey GL, Jansen RD, Ali FM, Camp VM, Kutner
MH, Schmidt F and Rudman D. “Tyramine Kinetics and Metabolism in Cirrhosis.” Journal of Clinical
Investigation, 64:413-420, 1979.
Heymsfield SB, Olafson RP, Kutner MH and Nixon DW. “A Radiographic Method of Quantifying
Protein-Calorie Undernutrition.” American Journal of Clinical Nutrition, 32:693-702, 1979.
Wolf SL, Basmajian J, Russe C and Kutner MH. “Normative Data on Low Back Mobility and Activity
Levels: Implications for Neuromuscular Reeducation.” American Journal of Physical Medicine, 58(5):217227, 1979.
Rudman D, Kutner MH, Goldsmith MA, Blackston RD and Bain RP. “Serum and Urine Polyamines in
Normal and Short Children.” Journal of Clinical Investigation, 64:1661-1668, 1979.
Fine RM, Chawla RK, Kutner MH and Rudman D. “Accumulation of Urinary Cancer- Related
Glycoprotein, EDC1, in Psoriasis.” The Journal of Investigative Dermatology, 73:264-265, 1979.
Nordlinger BM, Fulenwider JT, Ivey GL, Faraj BA, Ali FM, Kutner MH, Henderson JM and Rudman D.
“Tyrosine Metabolism in Cirrhosis.” Journal of Laboratory and Clinical Medicine, 94:832-840, 1979.
Nixon DW, Heymsfield SB, Cohen AE, Kutner MH, Ansley JD, Lawson DH and Rudman D. “ProteinCalorie Undernutrition in Hospitalized Cancer Patients.” American Journal of Medicine, 60:683-690, 1980.
Rudman D, Kutner MH, Chawla RK and Goldsmith RA. “Abnormal Polyamine Metabolism in Hereditary
Muscular Dystrophies.” Journal of Clinical Investigation, 65:95-102, 1980.
Rudman D, Goldsmith M, Kutner M and Blackston D. “Effect of Growth Hormone and Oxandrolone
Singly and Together on Growth Rate in Girls with X Chromosome Abnormalities.” Journal of Pediatrics,
96(1):132-134, 1980.
Nordlinger BM, Nordlinger DF, Fulenwider JT, Millikan WJ, Sones PJ, Kutner MH, Steele, R, Bain R and
Warren WD. “Angiography in Portal Hypertension: Clinical Significance in Surgery.” The American Journal
of Surgery, 139:132-141, 1980.
Smith III RB, Warren WD, Salam AA, Millikan WJ, Ansley JD, Kutner MH and Bain RP. “Dacron
Interposi-tion Shunts for Portal Hypertension: An Analysis of Morbidity Correlates.” Annals of Surgery,
192:9-17, 1980.
Rudman D, Dedonis JL, Fountain MT, Chandler JB, Gerron GG, Fleming GA and Kutner MH.
“Hypocitraturia in Patients with Gastrointestinal Malabsorption.” New England Journal of Medicine,
303:657-661, 1980.
Felner JM, Blumenstein BA, Schlant RC, Carter AD, Alimurung BN, Johnson MJ, Sherman SW, Klicpera
MW, Kutner MH and Drucker LW. "Sources of Variability in Echocardiographic Measurements." The
American Journal of Cardiology, 45:995-1004,1980.
Brogan DR and Kutner MH. “Comparative Analyses of Pretest-Posttest Research Designs.” The American
Statistician, 34:229-232, 1980.
Henderson JM, Stein SF, Kutner M, Wiles MB, Ansley JD & Rudman D. “Analysis of Twenty-three
Plasma Proteins in Ascites: The Depletion of Fibrinogen and Plasminogen.” Annals of Surgery, 192:739742, 1980.
Rudman D, Kutner MH, Goldsmith MA, Kenny J, Jennings H and Bain RP. “Further Observations
on Four Subgroups of Normal Variant Short Stature.” Journal of Clinical Endocrinology and Metabolism,
51:1378-1384, 1980.
Goldsmith MA, Bhatia SS, Kanto WP, Kutner MH and Rudman D. “Calcium Gluconate and Neonatal
Hypercalciuria.” American Journal of Diseases of Children, 135:538-543, 1981.
Bhatia SJS, Moffitt SD, Goldsmith MA, Bain RP, Kutner MH and Rudman D. “A Method of Screening for
Growth Hormone Deficiency Using Anthropometrics.” American Journal of Clinical Nutrition, 34:281-288,
1981.
Rypins EB, Fajman W, Sarper R, Henderson MJ, Kutner MH, Tarcan YA, Galambos JT and Warren WD.
“Radionuclide Angiography of the Liver and Spleen: A Noninvasive Method for Assessing Portal
Venous/Total Hepatic Blood Flow Ratio and Portasystemic Shunt Patency.” American Journal of Surgery,
574-579, 1981.
Nixon DW, Lawson D, Kutner M, Ansley J, Schwarz M, Heymsfield S, Chawla R, Cartwright TH
and Rudman D. “Hyperalimentation of the Cancer Patient with Protein- Caloric Undernutrition.” Cancer
Research, 41:2038-2045, 1981.
Nixon DW, Lawson DH, Kutner MH, Moffitt SD, Ansley J, Heymsfield SB, Lynn MJ, Wesley M,
Yancey R and Rudman D. “Effect of Total Parenteral Nutrition on Survival in Advanced Colon Cancer.”
Cancer Detection and Prevention, 4:421-427, 1981.
Nixon DW, Moffitt S, Lawson DH, Ansley J, Lynn MJ, Kutner MH, Heymsfield SB, Wesley M, Chawla R
and Rudman D. “Total Parenteral Nutrition as an Adjunct to Chemotherapy of Metastatic Colorectal
Cancer.” Cancer Treatment Reports, 65:121-128, 1981.
Rudman D, Kutner MH, Rogers CM, Lubin MF, Fleming GA and Bain RP. “Impaired Growth
164
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
Hormone Secretion in the Adult Population: Relation to Age and Adiposity.” Journal of Clinical Investigation,
67:1361-1369, 1981.
Henderson JM, Heymsfield SB, Horowitz J and Kutner MH. “Liver and Spleen Volume Measured by
Computerized Axial Tomography: Assessment of Reproducibility and the Changes Found following a
Selective Distal Splenorenal Shunt.” Radiology, 14:525-527, 1981.
Rudman D, Kutner MH, Blackston RD, Cushman RA, Bain RP and Henderson JA. “Children
with Normal Variant Short Stature: Treatment with Human Growth Hormone for Six Months.” New
England Journal of Medicine, 305:123-131, 1981.
Lawson DH, Nixon DW, Kutner MH, Heymsfield SB, Rudman D, Moffitt SD, Ansley J and Chawla RK.
“Enteral vs. Parenteral Nutrition Support in Cancer Patients.” Cancer Treatment Reports, 65:101-106, 1981.
50. Rypins EB, Henderson JM, Fajman W, Sarper R, Kutner M and Warren WD. “Portal VenousTotal Hepatic Flow Ratio by Radionuclide Angiography.” Journal of Surgical Research, 31:463-468, 1981.
51. Rudman D, Kutner M, Ansley J, Jansen R, Chipponi J and Bain RP. “Hypotyrosinemia,
Hypocystinemia, and Failure to Retain Nitrogen During Total Parenteral Nutrition of Cirrhotic
Patients.” Gastroenterology, 891:1025-1035, 1981.
Rudman D, Kutner MH, Redd SC, Waters WC, Gerron GG and Bleier J. “Hypocitraturia in
Calcium Nephrolithiasis.” Journal of Clinical Endocrinology and Metabolism, 55:1052 - 1057, 1982.
Gonnella C, Paris SV and Kutner MH. "Reliability in Evaluating Passive Intervertebral Motion."
Physical Therapy, 62:436-444, 1982.
Fitzgerald T, McGowan D, Kutner MH and Wenger NK. “Demographic Determinants of Success in the
Vocational Rehabilitation of Cardiac Patients.” Journal of Rehabilitation, 33 - 38, 1982.
Warren WD, Millikan WJ, Henderson JM, Wright L, Kutner MH, Smith RR, Fulenwider JJ, Salam AA and
Galambos JR. “Ten Years Portal Hypertensive Surgery at Emory.” Annals of Surgery, 195:530-542, 1982.
Henderson JM, Kutner MH and Bain RP. “First-order Clearance of Plasma Galactose: The Effect of Liver
Disease.” Gastroenterology, 83:1090-1096, 1982.
Henderson JM, Millikan WJ, Wright L, Kutner MH and Warren WD. “Quantitative Estimation of
Metabolic and Hemodynamic Hepatic Function: The Effects of Shunt Surgery.” Surgical Gastroenterology,
1:77-85, 1982.
Millikan Jr WJ, Henderson JM, Warren WD, Riepe SP, Kutner MH, Wright-Bacon L, Epstein C and
Parks RB. “Total Parenteral Nutrition with F080 in Cirrhotics with Subclinical Encephalopathy.” Annals of
Surgery, 197:48-58, 1983.
Jennings RH, Galloway JR, Brooke MN, Kutner MH, Rudman D, Vogel RL, Wardlaw CF and Gerron
GG. “Effects of Allopurinol in Duchene’s Muscular Dystrophy.” Archives of Neurology, 40:294 - 299,
1983.
Millikan Jr WJ, Henderson JM, Warren WD, Riepe SP, Davis RC, Hersh T, Wright-Bacon L, Long M and
Kutner MH. “Maintenance of Nutritional Competence After Gastric Partitioning for Morbid Obesity.” The
American Journal of Surgery, 146:619-625, 1983.
Faraj BA, Camp VM, Caplan DB, Ahmann PA and Kutner MH. “Abnormal Regulation of Pyridoxal 5'Phosphate in Reye's Syndrome.” Clinical Chemistry, 29:1832-1833, 1983.
Henderson JM, Millikan Jr WJ, Wright-Bacon L, Kutner MH and Warren WD. “Hemodynamic
Differences Between Alcoholic and Nonalcoholic Cirrhotics Following Distal Splenorenal Shunt – Effect on
Survival?” Annals of Surgery, 198:325-334, 1983.
Rudman D, Berry CJ, Riedeburg CH, Hollins BM, Kutner MH, Lynn MJ and Chawla RK. “Effects of
Opioid Peptides and Opiate Alkaloids on Insulin Secretion in the Rabbit.” Endocrinology, 112:1702-1710,
1983.
Rudman D, Hollins BM, Kutner MH, Moffitt SD and Lynn MJ. “Three Types of a- MelanocyteStimulating Hormone: Bioactivities and Half-Lives.” American Journal of Physiology, 245(Endocrinology
Metabolism 8):E47- E54, 1983.
Faraj BA, Gottlieb GR, Camp VM, Kutner MH and Lolies P. “Development of a Sensitive Radioassay of
Histamine for In Vitro Allergy Testing.” Journal of Nuclear Medicine, 25:56 -63, 1984.
Faraj BA, Caplan DB, Newman SL, Ahmann PA, Camp VM and Kutner MH.
“Hypercatecholaminemia in Reye's Syndrome.” Pediatrics, 73:482-488, 1984.
Chawla RK, Lewis FW, Kutner MH, Bate DM, Roy RGB and Rudman D. “Plasma Cysteine, Cystine, and
Glutathione in Cirrhosis.” Gastroenterology, 87:770 - 776, 1984.
Kutner NG, Fair PL and Kutner MH. “Assessing Depression and Anxiety in Chronic Dialysis Patients.”
Journal of Psychosomatic Research, 29:23-31, 1985.
Chawla RK, Berry C, Kutner MH and Rudman D. “Plasma Concentration of Transsulfuration
Pathway Product During Nasal Enteral and Intravenous Hyperalimentation of Malnourished Patients.”
American Journal of Clinical Nutrition, 42:577-584, 1985.
Millikan WJ, Henderson JM, Galloway JR, Warren WD, Matthews DE, McGhee A and Kutner MH.
“In Vivo Measurement of Leucine Metabolism with Stable Isotopes in Normal and Cirrhotic Subjects Fed
165
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.
Conventional and Branched-Chain Amino Acid Enriched Diets.” Surgery, 98:405-413, 1985.
Millikan WJ, Warren WD, Henderson JM, Smith RB, Salam AA, Galambos JT, Kutner MH and Keen JH.
“The Emory Prospective Randomized Trial: Selective versus Nonselective Shunt to Control Variceal
Bleeding”: Annals of Surgery, 201(6):712-722, 1985.
Faraj BA, Newman SL, Caplan DB, Ahmann PA, Kutner M, Ali FJ and Lindahl J. “Platelet Monoamine
Oxidose Activity in Reye's Syndrome.” Journal of Pediatric Gastroenterology and Nutrition, 4:532 - 536,
1985.
Epstein CM, Humphires LL, Alvarado C, Kutner MH and Ragab AS. “Sequential Quantitative EEG
Analysis in Acute Lymphocytic Leukemia of Children.” Clinical EEG, 16(4):208-212, 1985.
Rudman D, Kutner MH and Chawla RK. “The Short Child with Subnormal Plasma Somatomedin C.”
Pediatric Research, 19(10):975 - 980, 1985.
Rudman D, Chawla RK and Kutner MH. “Heterogeneity of Growth Hormone in the Nocturnal Serum of
Children." Pediatric Research, 19(10):981-985, 1985.
El-Khishen MA, Henderson JM, Millikan Jr WJ, Kutner MH and Warren WD. “Splenectomy is
Contraindicated for Thrombocytopenia Secondary to Portal Hypertension.” Surgery, Gynecology and
Obstetrics, 160:237-238, 1985.
Faraj BA, Camp VM, Murray DR, Kutner M, Hearn J and Nixon D. “Plasma L-Dopa in the Diagnosis of
Malignant Melanoma.” Clinical Chemistry, 32:159 - 161, 1986.
Brogan D and Kutner MH. “Graduate Service Statistics Courses.” The American Statistician, 40(3):252-254,
1986.
Ezzat FA, Abu-Elmagd KM, Aly IY, Aly MA, Fathy OM, El-Barbary MH, Bahgat OO, Salam AA and
Kutner MH. “Distal Splenorenal Shunt for Management of Variceal Bleeding in Patients with Schistosomal
Hepatic Fibrosis.” Annals of Surgery, 204:566 - 573, 1986.
Affarah HB, Hall WD, Heymsfield SB, Kutner M, Wells JO and Tuttle EP. “High Carbohydrate Diet:
Antinatriuretic and Blood Pressure Response in Normal Men.” American Journal of Clinical Nutrition, 44:341
-348, 1986.
Warren WD, Henderson JM, Millikan WJ, Galambos JT, Brooks WS, Riepe SP, Salam AA and Kutner MH.
“Distal Splenorenal Shunt Versus Endoscopic Sclerotherapy for Long-term Management of Variceal
Bleeding.” Annals of Surgery, 203:454 - 462, 1986.
Henderson JM, Codner MA, Hollins B, Kutner MH and Merrill AH. “The Fasting B6 Vitamer Profile
and Response to a Pyridoxine Load in Normal and Cirrhotic Subjects.” Hepatology, 6(3):464 - 471, 1986.
Sarper RM, Burdette EC, Crowgey SR, Malveaux EJ and Kutner M. “Technetium 99m Pertechnetate
Measurement of Renal Blood Flow Distribution.” American Journal of Physiologic Imaging, 1:129 - 133,
1986.
Faraj BA, Caplan DB, Camp VM, Pilzer E and Kutner M. “Low Levels of Pyridoxal 5'- Phosphate in
Patients with Cystic Fibrosis.” Pediatrics, 78(2):278 - 282, 1986.
Warren WD, Millikan WJ, Henderson JM, Abu-Elmagd KM, Galloway JR, Shires GT, Richards WO,
Salam AA and Kutner MH. “Splenopancreatic Disconnection: Improved Selectivity of Distal Splenorenal
Shunt.” Annals of Surgery, 204(4):346 - 355, 1986.
Kutner NG, Brogan DR and Kutner MH. “End-Stage Renal Disease Treatment Modality and Patient's
Quality of Life.” American Journal of Nephrology, 6:396-402, 1986.
Rudman D and Kutner MH. “Effect of bh-Endorphin on Release of Insulin by Rabbit Pancreas in
Response to Four Secretagogues: Comparison with Somatostatin and Epinephrine.” Hormone Metabolism
Research, 18:365-368, 1986.
Noe B, Henderson JM and Kutner MH. “Alternative Methods Evaluated for Assaying Low Concentrations
of Galactose in Plasma.” Clinical Chemistry, 33:420, 1987.
Faraj BA, Lenton JD, Kutner M, Camp VM, Stammers TW, Lee SR, Lolies PA and Chandora
“Prevalence of Low Monoamine Oxidase Function in Alcoholism.” Alcoholism: Clinical and Experimental
Research, Volume 11(5):464-467, 1987.
Kutner NG and Kutner MH. “Ethnic and Residence Differences Among Poor Families: A Research
Note.” Journal of Comparative Family Studies, 18(3):463-470, 1987.
Lumsden AB, Henderson JM and Kutner MH. “Endotoxin Levels Measured by a Chromogenic Assay in
Portal, Hepatic and Peripheral Venous Blood in Patients with Cirrhosis.” Hepatology, 8(2):232 - 236, 1988.
Smith TF, Muldoon MF, Bain RP, Wells EL, Tiller TL, Kutner MH, Schiffman G and PandyJP. “Clinical
Results of a Prospective, Double-Blind, Placebo-Controlled Trial of Intravenous g-Globulin in Children with
Chronic Chest Symptoms.” Monographs in Allergy, 23:168 - 176. (Karger, Basel 1988).
Flores L, Pais R, Buchanan I, Arnelle D, Camp VM, Kutner M, Faraj BA, Eckman J and Ragab
“Pyridoxal 5'-Phosphate Levels in Children with Sickle Cell Disease.” The American Journal of Pediatric
Hematology/Oncology, 10(3):236-240, 1988.
Pearson TC, Henderson JM, DePuey G, Kutner M & Warren WD. “Cardiac Index & Left Ventricular
Function Changes in Cirrhosis Measured by Radionuclide Angiocardiography.” Digestive Surgery, 5:151-155,
166
95.
96.
97.
98.
99.
100.
101.
102.
103.
104.
105.
106.
107.
108.
109.
110.
111.
112.
113.
114.
115.
116.
1988.
Nixon DW, Kutner MH, Heymsfield SB, Foltz AJ, Carty C, Seitz S, Casper K, Evans WK, Jeejeebhoy KN,
Daly JM, Heber DM, Poppendiek H and Hoffman FA. “Resting Energy Expenditure in Lung and Colon
Cancer.” Metabolism, 37:1059 - 1064, 1988.
Bonkovsky HL, Hartle DK, Mellen BG, Kutner M & Galambos J. “Plasma Concentrations of
Immunoreactive Atrial Natriuretic Peptide in Hospitalized Cirrhotic & Noncirrhotic Patients: Evidence for a
Role of Deficient Atrial Natriuretic Peptide in Pathogenesis of Cirrhotic Ascites.” Amer. J. of
Gastroenterology, 83:531-535, 1988.
Chawla RK, Wolf DC, Kutner MH and Bonkovsky HL. “Choline May be an Essential Nutrient in
Malnourished Patients with Cirrhosis.” Gastroenterology, 97:1514 - 1520, 1989.
Alvarado GS, Findley HW, Chan WC, Hnath RS, Abdel-Mageed A, Pais RC, Kutner MH and Ragab AH.
“Natural Killer Cells in Children with Malignant Solid Tumors: Effect of Recombinant Interferon-a and
Interleukin-2 on Natural Killer Cell Function Against Tumor Cell Lines.” Cancer, 63(1):83 - 89, 1989.
Epstein CM, Trotter CJ, Averbook A, Freeman S, Kutner MH and Elsas LJ. “EEG Mean Frequencies
are Sensitive Indices of Phenylalanine Effects on Normal Brain.” Electroencephalography and Clinical
Neurophysiology, 72:133 - 139, 1989.
Lynn MJ, Waring GO, Nizam A, Kutner MH, et al. “Symmetry of Refractive and Visual Acuity Outcome
in the Prospective Evaluation of Radial Keratotomy (PERK) Study.” Refractive Corneal Surgery, 5:75 - 81,
1989.
Miller LR, Soffer O, Nassar VH and Kutner MH. “Acquired Renal Systic Disease in End- Stage Renal
Disease: An Autopsy Study of 155 Cases.” American Journal of Nephrology, 9:322 - 328, 1989.
Henderson JM, Scott SS, Merrill AH, Hollins B and Kutner MH. “Vitamin B6 Repletion in Cirrhosis with
Oral Pyridoxine: Failure to Improve Amino Acid Metabolism.” Hepatology, 9:582 - 588, 1989.
Faraj BA, Camp VM, Davis DC, Lenton JD & Kutner M. "Evaluation of Plasma Salsolinol Sulfate in
Chronic Alcoholics as Compared to Non-alcoholics." Alcoholism: Clinical and Experimental Research,
13:155-163, 1989.
104.Henderson JM, Millikan WJ, Hooks M, Noe B, Kutner MH and Warren WD. “Increased Galactose
Clearance After Liver Transplantation: A Measure of Increased Blood Flow Through a Denervated Liver?”
Hepatology, 10:288-291, 1989.
Henderson JM, Warren WD, Millikan WJ, Galloway JR, Kawasaki S and Kutner MH. “Distal Splenorenal
Shunt with Splenopancreatic Disconnection.” Annals of Surgery, 210:332-341, 1989.
Slovis CM, Negus RA, Amerson SM and Kutner MH. “Bedside Cerebrospinal Fluid Glucose.” Annals of
Emergency Medicine, 18:931 - 933, 1989.
Maroni BJ, Haesemeyer RW, Kutner MH and Mitch WE. “Kinetics of System A Amino Acid Uptake by
Muscle: Effects of Insulin and Acute Uremia.” American Journal of Physiology: Renal Fluid an Electrolyte
Physiology, 258:F1304-F1310, 1990.
Waring GO, Lynn MJ, Fielding B, et al (PERK Study Group). "Results of the Prospective Evaluation of
Radial Keratotomy (PERK) Study 4 Years After Surgery for Myopia." Journal of the American Medical
Association, 263(8):1083-1091, 1990.
Henderson JM, Kutner MH, Millikan WJ, Galambos JJ, Riepe SP, Brooks S, Bryan C and Warren WD.
“Endoscopic Variceal Sclerosis Compared to Distal Splenorenal Shunt to Prevent Recurrent Variceal Bleeding
in Cirrhosis.” Annals of Internal Medicine, 112(4):262 - 269, 1990.
Newby FD, DiGirolamo M, Cotsonis GA and Kutner MH. “Model of Spontaneous Obesity in Aging Male
Wistor Rats.” American Journal of Physiology, 259:R1117- R1125, 1990.
Waring GO, Lynn MJ, Stahlman ER, Kutner MH, Culbertson W, Laibson PR, Lindstrom RP, McDonald
MB, Myers WD, Obstbaum SA, Rowsey JJ, Smith RE and the Prospective Evaluation of Radial Keratotomy
Study Group. “Stability of Refraction During Four Years After Radial Keratotomy in the Prospective
Evaluation of Radial Keratotomy Study.” American Journal of Ophthalmology, 111:133 - 144, 1991.
Faraj BA, Camp VM and Kutner M. “Interrelationship Between Activation of Dopaminergic Pathways and
Cerebrospinal Fluid Concentration of Dopamine Tetrahydroisoquinoline Metabolite Sulsolinol in Humans:
Preliminary Findings.” Alcoholism: Clinical and Experimental Research, 15(1):86 - 89, 1991.
Zumpe D, Bonsall RW, Kutner MH and Michael RP. “Medroxyprogesterone Acetate, Aggression, &
Sexual Behavior in Male Cynomolgus Monkeys (Macaca fascicularis).” Hormones and Behavior, 25:394 - 409,
1991.
Henderson JM, Mackay GJ, Lumsden AB, Hussein MA, Brouillard R & Kutner MH. “The Effect of Liver
Dene-rvation on Hepatic Hemodynamics During Hypovolemic Shock in Swine.” Hepatology, 15(1):130-133,
1992.
Henderson JM, Mackay GJ, Hooks M, Chezmar JL, Galloway JR, Dodson, TF and Kutner MH. “High
Cardiac Output of Advanced Liver Disease Persists After Orthotopic Liver Transplantation.” Hepatology,
15(2):258 - 262, 1992.
Hooks MA, Perlino CA, Henderson JM, Millikan WJ Jr and Kutner MH. “Prevalence of Invasive
167
117.
118.
119.
120.
121.
122.
123.
124.
125.
126.
127.
128.
129.
130.
131.
132.
133.
134.
135.
136.
137.
Cytomegalovirus Disease with Administration of Muromonab CD-3 in Patients Undergoing Orthotopic
Liver Transplantation.” Annals of Pharmacotherapy, 26:617 - 620, 1992.
Henderson JM, Gilmore GT, Mackay GJ, Galloway JR, Dodson TF and Kutner MH.
“Hemodynamics During Liver Transplantation: The Interactions Between Cardiac Output and Portal
Venous and Hepatic Arterial Flows.” Hepatology, 16:715-718, 1992.
Smith TF, Sanchez-Legrand F, McKean LP, Kutner MH, Cragoe Jr EJ and Eaton DC. “Role of Sodium in
Mediator Release From Human Basophils.” Journal of Allergy and Clinical Immunology, 89:978-986,
1992.
Henderson JM, Gilmore GT, Hooks MA, Galloway JR, Dodson TF, Hood MM, Kutner MH and Boyer
TD. “Selective Shunt in the Management of Variceal Bleeding in the Era of Liver Transplantation.” Annals
of Surgery, 216:248-255, 1992.
Spina GP, Henderson JM, Rikkers LF, Teres J, Burroughs AK, Conn HO, Pagliaro L, Santambrogio
R, Ascione A, Bordas JM, Scott BW, Buchi KM, Burnett DA, Cormier RA, Galambos JT, Kutner MH,
Millikan WJ, Opocher E, Pisani A, Riepe SP, Visa J, and Warren WD. “Distal spleno-renal shunt versus
endoscopic sclerotherapy in the prevention of variceal rebleeding. A meta-analysis of 4 randomized clinical
trials.” Journal of Hepatology, 16:338-345, 1992.
Newcom SR, Ward M, Napoli VM and Kutner M. “Treatment of Human Immunodeficiency VirusAssociated Hodgkin Disease. Is There a Clue Regarding the Cause of Hodgkin Disease?” Cancer, 71:31383145, 1993.
Henderson JM, Mackay GJ, Kutner MH and Noe B. “Volumetric and Functional Liver Blood Flow are
Both Increased in the Human Transplanted Liver.” Journal of Hepatology, 17:204-207, 1993.
Faraj BA, Camp VM, Davis DC, Kutner M, Cotsonis GA and Holloway T. “Elevated Concentrations of
Dopamine Sulfate in Plasma of Cocaine Abusers.” Biochemical Pharmacology, 46:1453-1457, 1993.
Green RC, Green J, Harrison JM and Kutner MH. “Screening for Cognitive Impairment in Older
Individuals. Validation Study of a Computer-Based Test.” Archives of Neurology, 51:779 - 786, 1994.
King SB III, Lembo NJ, Weintraub WS, Kosinski AS, Barnhart HX, Kutner MH, Alazraki NP, Guyton
RA & Zhao XQ for the Emory Angioplasty Versus Surgery Trial (EAST). “A Randomized Trial Comparing
Coronary Angioplasty with Coronary Bypass Surgery.” New England Journal of Medicine, 331:1044 - 1050,
1994.
Boyer TD, Kokenes DD, Hertzler G, Kutner MH and Henderson JM. “Effect of Distal Splenorenal
Shunt on Survival of Patients with Primary Biliary Cirrhosis.” Hepatology, 20:1482 - 1486, 1994.
Kutner MH. “The Computer Analysis of Factorial Experiments with Nested Factors.” vited response to
Dallal, G.E. (1992), The American Statistician, 46, 240. The American Statistician, 48:147, 1994.
Weintraub WS, Boccuzzi SJ, Klein JL, Kosinski AS, King SB 3rd, Ivanhoe R, Cedarholm JC, Stillabower ME,
Talley JD, DeMaio SJ, et al. “Lack of effect of lovastatin on restenosis after coronary angioplasty. Lovastatin
Restenosis Trial Study Group”. New England Journal of Medicine, 331:1331 - 1337, 1994.
King SB III, Lembo NJ, Weintraub WS, Kosinski AS, Barnhart HX, Kutner MH for the EAST
Investigators. “Emory Angioplasty Versus Surgery Trial (EAST): Design, Recruitment, and Baseline
Description of Patients.” The American Journal of Cardiology, 75:42C - 59C, 1995.
Ellis SG, Miller DP, Brown KJ, Omoigui N, Howell GL, Grierson J, Kutner M & Topol EJ. “In-hospital
Cost of Percutaneous Coronary Revascularization: Critical Determinants & Implications.” Circulation, 92:741747, 1995.
Robinson K, Mayer E, Miller DP, Green R, Gupta A, Kottke-Merchant K, Savon S, Selhub J, Nissen S,
Topol E, Kutner M and Jacobsen DW. “Hyperhomocysteinemia and Vitamin B6 Deficiency: Common
and Independent Reversible Risk Factors for Coronary Artery Disease.” Circulation, 92:2825 - 2830, 1995.
Wolf SL, Barnhart HX, Kutner NG, McNeely E, Coogler C, Xu T and the Atlanta FICSIT Group.
“Reducing Frailty and Falls in Older Persons: An Investigation of Tai Chi and Computerized Balance
Training.” Journal of American Geriatric Society, 44:489-497, 1996.
Qu Y, Tan M and Kutner MH. “Random Effects Models in Latent Class Analysis for Evaluating
Accuracy of Diagnostic Tests.” Biometrics, 52:797 - 810, 1996.
Robinson K, Gupta A, Dennis V, Arheart K, Chaudhary D, Green R, Vigo P, Mayer EL, Selhub J,
Kutner M and Jacobsen DW. “Hyperhomocysteinemia Confers an Independent Increased Risk of
Atherosclerosis in End-Stage Renal Disease and Is Closely Linked to Plasma Folate and Pyridoxine
Concentrations.” Circulation, 94:2743-2748, 1996.
Tan M, Qu Y and Kutner MH. “Model Diagnostics for Marginal Regression Analysis of Correlated
Binary Data." Communications in Statistics Series B, 26:539 - 558, 1997.
The EPILOG Investigators. Platelet Glycoprotein IIb/IIIa Receptor Blockade and Low-Dose Heparin
During Percutaneous Coronary Revascularization. New England Journal of Medicine, 336(24):1689-1696,
1997.
Tan M, Xiong X and Kutner MH. “Clinical Trial Designs Based on Sequential Conditional Probability
Ratio Tests and Reverse Stochastic Curtailing.” Biometrics, 54:684-697, 1998.
168
138.
139.
140.
141.
142.
143.
144.
145.
146.
147.
148.
149.
150.
151.
152.
153.
154.
155.
156.
157.
158.
159.
Kressig RW, Wolf SL, Sattin RW, O’Grady M, Greenspan A, Curns A and Kutner MH. “Associations of
Demographic, Functional, and Behavioral Characteristics with Activity- Related Fear of Falling Among Older
Adults Transitioning to Frailty.” Journal of American Geriatrics Society, 49(11):1456-1462, 2001.
Wolf, S.L., Sattin. R.W., O’Grady, M., Freret, N., Ricci, L., Greenspan. A.I., Xu, T. and Kutner, M.H.
“A Study Design to Investigate the Effect of Intense Tai Chi in Reducing Falls among Older Adults
Transitioning to Frailty.” Controlled Clinical Trials, 22(6):689-704, 2001.
Xiong, X., Tan, M. and Kutner, M.H. “Computational Methods for Evaluating Sequential Tests and Posttest Estimation via the Sufficienncy Principle.” Statistica Sinica, 12(4):1027-1041, 2002.
Gassman, JL, Greene, T, Wright, Jr, JT, Agodoa, L, Bakris, G, Beck, GJ, Douglas, J, Jamerson, K, Lewis,
J, Kutner, M, Randall, OS, Wang, S-R & AASK Group. “Design and Statistical Aspects of the African
American Study of Kidney Disease and Hypertension (AASK).” J Am Soc Nephrol, 14: S154 - S165, 2003.
Kapasi, Z.F., Ouslander, J.G., Schnelle, J.F., Kutner, M., and Fahey, J.L. “Effects of an Exercise
Intervention on Immunologic Parameters in Frail Elderly Nursing Home Residents.” Journal of Gerontology:
Medical Sciences, 58A (7): 636 - 643, 2003.
Wolf, S.L., Sattin, R.W., Kutner, M., O’Grady, M., Greenspan, A.I., and Gregor, R.J. “Intense Tai
Chi Exercise Training and Fall Occurrences in Older, Transitionally Frail Adults: A Randomized
Control Trail.” Journal of the American Geriatric Association, 51:1693 - 1701, 2003.
Johnson, T.M., Jones, K., Williford, W., Kutner, M., Issa, M., and Lepor, H. “Changes in Nocturia from
Medical Treatment of Benign Prostatic Hyperplasia: Secondary Analysis of the Department of Veterans
Affairs Cooperative Study Trial.” Journal of Urology, 170: 145 - 148, 2003.
Van De Water, M.S., Kutner, M., Parmelee, P.A., Johnson, T. “Which long-term care residents
should be asked to complete a customer satisfaction survey?” Journal Am Med Dir Assoc. 4:257 - 263, 2003.
Kressig, R.W., Gregor, R.J., Oliver, A., Waddell, D., Smith, W., O’Grady, M., Curns, A.T., Kutner, M.,
Wolf, S.L. “Temporal and Spatial Features of Gait in Older Adults Transitioning to Frailty.” Journal of Gait
and Posture, 20:30 - 35, 2004.
Endeshaw, Y., Johnson, T., Kutner, M., Ouslander, J., and Bliwise, D. “Sleep-Disordered Breathing and
Nocturia in Older Adults.” Journal of the American Geriatrics Society, 52:957-960, 2004.
Pisoni, R.L., Gillespie, B.W, Dickinson, D.M., Chen, K., Kutner, M.H., and Wolfe, R.A. “The Dialysis
Outcomes and Practice Patterns Study (DOPPS): Design, Data Elements, and Methodology. American
Journal of Kidney Disease, 44 (5 Suppl 2):7 - 15, 2004.
Greco, K.E., Deaton, C., Kutner, M., Schnelle J.F., and Ouslander, J.G. “Psychoactive Medications and
Actigraphically Scored Sleep Quality in Frail Nursing Home Patients”. J American Medical Directors
Association, 5(4):223 - 227, 2004.
Sattin, R., Easley, K., Wolf, S., Chen, Y. and Kutner, M. Reduction in Fear of Falling Through Intense Tai Chi
Exercise Training in Older, Transitionally Frail Adults, Journal of the American Geriatrics Society, 53(7):1168
-1178, 2005.
Ouslander, J.G., Griffiths, P., McConnell, E., Riolo, L., Kutner, M. and Schnelle, J. “Functional Incidental
Training: A Randomized, Controlled, Crossover Trial in Veterans Affairs in Nursing Homes.” Journal of the
American Geriatrics Society, 53(7):1091 - 1100, 2005.
Kitayama, N., Vaccarino, V., Kutner, M., Weiss, P. and Bremner, D. “Magnetic Resonance Imaging (MRI)
Measurement of Hippocampal Volume in Posttraumatic Stress Disorder: A Metanalysis.” Journal of Affective
Disorders, 88(1):79 - 86, 2005.
Henderson, J.M., Boyer, T.D., Kutner, M.H., Galloway, J.R., Rikkers, L.F., Jeffers, L.J., Abu-Elmagd, K.,
Connor, J.: DIVERT Study Group. “Distal Slenorenal Shunt versus Transjugular Intrahepatic Portal
Systematic Shunt for Variceal Bleeding: A Randomized Trial.” Gastroenterology, 130(6):1643 - 1651, 2006.
Wolf, S.L., O’Grady, M., Easley, K.A., Guo, Y., Kressig, R.W., and Kutner, M.H. “The influence of intense
tai chi training on physical performance and hemodynamic outcomes in transitionally frail adults.” Journals of
Gerontology: Medical Sciences Series A – Biological Sciences & Medical Sciences, 61(2): 184 - 189, 2006.
Puskas, J.D., Kilgo, P.D., Kutner, M., Pusca, S.V., Lattouf, O., and Guyton, R.A. “Off-pump techniques
disproportionately benefit women and narrow the gender disparity in outcomes after coronary artery bypass
surgery.” Circulation, 116 (11): 1192 - 1199, 2007.
Endeshaw, Y.W., Unruh, M., Kutner, M., Ouslander, J., Newman, A., and Bliwise, D. “Sleep disordered
breathing and frailty-Gender differences.”Journal of the American Geriatrics Society, 56(4): S187 - S187, 2008.
Boyer, T.D., Henderson, J.M., Heerey, A.M., Arrigain, S., Konig, V., Connor, J., Abu- Elmagd, K., Galloway,
J., Rikkers, L.F., Jeffers, L., DIVERT Study Group. “Cost of preventing variceal rebleeding with transjugular
intrahepatic portal systemic shunt and distal splenorenal shunt.” Journal of Hepatology, 48 (3): 407- 414,
2008.
Lucey, M.R., Connor, J.T., Boyer, T.D., Henderson, J.M., Rikkers, L.F., DIVERT Study Group. “Alcohol
consumption by cirrhotic subjects: patterns of use and effects on liver function.” American Journal
Gastroenterol, 103 (7): 1698 - 1706, 2008.
Endeshaw, Y.W., White, W.B., Kutner, M., Ouslander, J.G., and Bliwise, D.L. “Sleep- disordered breathing
169
160.
161.
162.
163.
164.
165.
166.
and 24-hour blood pressure pattern among older adults.” Journal of Gerontology Series A: Biological
Sciences and Medical Sciences, 64:280 - 285, 2009.
Weinberg, J.M., Appel, L.J., Bakris, G., Gassman, J.J., Greene, T., Kendrick, C.A., Wang, X., Lash, J., Lewis,
J.A., Pogue, V., Thornley-Brown, D., Phillips, R.A., African American Study of Hypertension and Kidney
Disease Collaborative Research Group. “Risk of hyperkalemia in nondiabetic patients with chronic kidney
disease receiving antihypertensive therapy.” Arch Internal Medicine, 169: 1587 - 1594, 2009.
Contreras, G., Hu, B., Astor, B.C., Greene, T., Erlinger, T., Kusek, J.W., Lipkowitz, M., Lewis, J.A.,
Randall, O.S., Herbert, L., Wright, J.T., Jr., Kendrick, C.A., Gassman, J., Bakris, G., Kopple, J.D., Appel, L.J.,
“African-American Study of Kidney Disease, and Hypertension Study Group.” Journal of American Society
of Nephrology, 21: 2131 - 2142, 2010.
Ji, S., Long, Q., Newport, D.J., Na, H., Knight, B., Zach, E.B., Morris, N.J., Kutner, M., Stowe, Z.N., “Validity
of depression rating scales during pregnancy and the postpartum period: impact of trimester and parity.”
Journal of Psychiatric Research, 45: 213 - 219, 2011.
Kauh J, Chanel-Vos C, Escuin D, Fanucchi MP, Harvey RD, Saba N, Shin DM, Gal A, Pan L, Kutner M,
Ramalingam SS, Bender L, Marcus A, Giannakakou P, Khuri FR. “Farnesyl transferase expression
determines clinical response to the docetaxel-lonafarnib combination in patients with advanced
malignancies.” Cancer, 2011 Mar 1. doi: 10.1002/cncr.26004. [Epub ahead of print].
Josephson CD, Castillejo MI, Caliendo AM, Waller EK, Zimring J, Easley KA, Kutner M, Hillyer CD,
Roback JD. “Prevention of transfusion-transmitted cytomegalovirus in low-birth weight infants≤15(00 g)
using cytomegalovirus -seronegative and leukoreduced transfusions.” Transfus Med Rev. 25:125-132, 2011.
Terry, PD, Goyal, A, Phillips, LS, Superak, HM, Kutner, MH “Design and rationale of a randomized
controlled trial of melatonin supplementation in men and women with the metabolic syndrome” Open Access
Journal of Clinical Trials 2013:5 51-59.
Goyal, A, Terry, PD, Superak, HM, Nell-Dybdahl, CL, Chowdhury, R,. Phillips, LS, Kutner, MH
“Supplementation to treat the metabolic syndrome: a randomized controlled trial” Journal of Diabetology &
Metabolic Syndrome in press
CITATIONS AND ACKNOWLEDGMENTS
• Tabulation of Hermite Polynominals (Table 2) in Pearson, ES and Hartley HO, Biometrika Tables for
Statisticians, Volume II, 1972.
• Morgan SL and Deming SN. Simplex Optimization of Analytical Chemical Methods.” Analytical Chemistry,
46:1178-1180, 1974.
• Michael RP, Bonsall RW and Warner P. “Human Vaginal Secretions: Volatile Fatty Acid Content.” Science,
186:1217-1219, 1974.
• 1974 AMSTAT paper cited in Biomedical Computer Programs (BMDP Manual) and SAS User's Guide.
• Zumpe D and Michael RP. “Effects of Ejaculations by Males on the Sexual Invitations of Female Rhesus
Monkeys (Macaca mulatta).” Behavior, LX: 260-277, 1977.
• Bonsall RW, Zumpe D and Michael RP. “Menstrual Cycle Influences on Operant Behavior of Female
Rhesus Monkeys.” Journal of Comparative and Physiological Psychology, 92:846-855, 1978.
• Michael RP and Zumpe D. “Potency in Male Rhesus Monkeys: Effects of Continuously Receptive Females.”
Science, 200:451-453, 1978.
• Wolf SL, Ariel GB, Saar D, Penny MA and Railey P. “The Effect of Muscle Stimulation during Resistive
Training on Performance Parameters.” The American Journal of Sports Medicine, 14:18-23, 1986.
• Kutner NG, Brogan D, Fielding B and Hall WD. “Older Renal Dialysis Patients and Quality of Life.” Dialysis and
Transplantation, 20(4):171-175, 1991.
LETTERS TO EDITOR
1. Kutner MH. “Improving Refereeing Policies.” The American Statistician, 29(2):110, 1975.
2. Brown AC, Olkowski ZL, McLaren JR and Kutner MH. “Alopecia Areata and Vitiligo Associated with Down's
Syndrome.” Archives of Dermatology, 113:1296, 1977.
3. Rudman D, Kutner MH, Blackston RD and Patterson JH. “Normal Variant Short Stature.” New England
Journal of Medicine, 305(19):1153-1154, November, 1981.
4. Ingram C, Frederickson E and Kutner MH. “Inappropriateness of Statistical Methods Used in Evaluating
Postanesthetic Hepatic Injury.” Anesthesia and Analgesia, 61(8):728, August, 1982.
5. Henderson JM and Kutner MH. “Galactose Clearance as a Measure of Hepatic Blood Flow.” Gastroenterology,
85:986-988, September, 1983.
6. Henderson JM and Kutner MH. “An Analysis of Survival and Treatment Failure Following Abdominoperineal
and Sphincter-saving Resection in Dukes' B and C Rectal Carcinoma: A Report of the NSABP Clinical Trials.”
Annals of Surgery, 206(4):224-226, August, 1987.
170
7. Henderson JM, Kutner MH and Warren WD. “Do Surgeons Led by Surgeons Operate Better Than Internist-led
Surgeons?” Gastroenterology, 93(3):666-667, September, 1987.
8. Henderson JM, Kutner MH and Warren WD. “Sclerotherapy vs. Distal Splenorenal Shunt in the Elective
Treatment of Variceal Hemorrhage: A Randomized Controlled Trial.” Hepatology, 8(2):441-442, 1987.
9. Henderson JM, Kutner MH and Noe B. “Galactose Clearance and Liver Blood Flow.”
Gastroenterology, 95(4):1157-1158, 1988.
10. Kutner MH, Rao JS. “Prediction of Hospital Mortality Rates.” Annals of Internal Medicine, 127(9):846847, 1997.
PRESENTATIONS, SEMINARS AND SHORT COURSES
August 2015
Invited panelist at the ASA Joint Statistical Meeting in Seattle, to discuss how to be an effective collaborating
statistician
Oct 30, 2014
Invited seminar speaker at the University of North Carolina, Wilmington, NC on the analysis of fixed effects models
with missing data in some cells
April 30, 2014
Invited panelist to discuss teaching of introductory statistics courses to non-statistics majors at Georgia ASA
Chapter meeting
June 2, 2014
Invited speaker at the 50th Anniversary at the SRCOS SRC in Galveston, TX, June 1-4, 2014 meeting to discuss the
role that SRCOS has played in developing academic programs in statistics/biostatistics in the South.
Aug 2, 2014
Invited speaker at the ASA Joint Statistical Meetings in Boston, MA, August 2 - 7, 2014 to discuss the growth of
statistics academic programs in the South and its association with ASA.
June 6, 2011
Keynote Dinner Speaker, Southern Regional Council on Statistics Summer Research Conference: “Recollections and
Reflections.”
June 5, 2011
Organizer and Panel Discussant, Southern Regional Council on Statistics Summer Research Conference,
“Teaching Introductory Statistics/Biostatistics Courses for Non-Majors.”
July 2010-13
Two 2-hour lectures each year to Summer Institute for Training in Biostatistics (SIBS) program attendees on
research projects/designs
August 5, 2009 Invited Panel Discussant, JSM 2009, Mu Sigma Rho Session.
August 3, 2009 Invited panel session JSM, Title: “Directing a Biostatistics Core in Biomedical Research.”
April 2-3, 2009 Keynote Speaker, “Innovations in Design, Analysis, and Dissemination: Frontiers in Biostatistical Methods.”
Cerner-Kansas University Medical College – ASA Biostatistics Symposium, Kansas City, KS.
Jan 16-17, 2009 Short Course: Design and Analysis of Clinical Studies, Shriner’s Hospitals, Clearwater Beach, FL
June 20, 2007
“How to Design a Research Study”, Summer Interns, Division of Geriatrics, Atlanta, GA
April 24, 2007
“Analysis of Fixed Effects ANOVA Models with Missing Cells”, Medical College of GA, Augusta, GA
April 20, 2007
“Analysis of Fixed Effects ANOVA Models with Missing Cells”, The Hocking Lecture, Texas A&M
June 20, 2006
“How to Design a Research Study”, Summer Interns, Division of Geriatrics, Atlanta, GA
April 21, 2006
“Analysis of Fixed Effects ANOVA Models with Missing Cells”, Department of Mathematical Sciences, Bowling
Green University, Bowling Green, OH
Nov 30, 2005
“Past, Present and Future of Biostatistics”, Georgia Chapter, ASA, Atlanta, GA
“Statistical Collaboration and Consulting Within the Health Sciences”, Division of Pulmonary Medicine, Emory
Oct 20, 2005
University, Atlanta, GA
Oct 6, 2005
“Intense Tai Chi Exercise Training and Fall Occurrences in Older, Transitionally Frail Adults: Trial Designs and
Outcomes” University of Texas Southwestern Medical School, Dallas, TX
Aug 29, 2004
Invited Speaker: “Outliers and Their Effects on the Scientific Literature”, Winship Cancer Institute,
Atlanta, GA
Aug 11, 2004
Invited Speaker: “Statistical Consulting within the Medical Sciences”, Joint Statistical Meeting, Toronto, Canada
Jun 16, 2004, July 1, 2003
“Reading the Medical Literature”, AFAR Summer Research Students, Center for Health in Aging”, Wesley Woods
Health Center, Atlanta, GA
Nov 19, 2002
“Biostatistical Considerations in Rehabilitation Research”, Rehabilitation Residents and Fellows, Rehabilitation
Medicine Department, Emory University
Oct 30, 2002
“Biostatistical Collaboration: the Good, the Bad and the Ugly”, Center for Research on Symptoms, Symptom
Interactions, and Health Outcomes, Emory University Nell Hodgson Woodruff School of Nursing
“A Unified Regression Approach for Fixed Effects ANOVA Models with Missing Cells”, Department of
Oct 16, 2002
Biostatistics, Emory University
Sept 17, 2002
“Biostatistical Support”, Clinical Trials Office Symposium
April 2, 2002
Invited Speaker: “Outliers”, Southeastern Family Medicine and Primary Care Research Conference, Savannah,
Georgia (Mercer School of Medicine).
Dec 12, 2001
Invited Seminar: “Outliers and Their Effects.” VA Rehab R & D, Atlanta, Georgia.
May 11, 2001
Invited Workshop Speaker: “Interpretation of Diagnostic Tests.” Southeastern Family Medicine and Primary Care
Research Conference, Savannah, Georgia.
March 28, 2001 Invited Seminar: “Observational versus Experimental Studies: That is the Question.” VA Rehab R & D, Atlanta,
Georgia.
Aug12-13, 2000 Invited 2 Day Short Course: “Logistic Regression Analysis.” Joint Statistical Meeting, Indianapolis, Indiana
(with C. Nachtsheim)
March 8, 2000
Invited Seminar: “Design and Statistical Aspects of the African American Study of Kidney Disease and
171
Nov 3, 1999
July 13, 1999
May 19, 1999
March 3, 1999
Dec 14, 1998
Oct 29, 1998
Oct 21, 1998
Aug 27, 1998
July 24, 1998
April 29, 1998
April 20, 1998
March 27, 1998
Mar18-20, 1998
Dec 3, 1997
Nov 1, 1997
Oct 31, 1997
Oct 29, 1997
July 28, 1997
June 21, 1997
June 10, 1997
June 9, 1997
June 6, 1997
June 5, 1997
Mar19-21, 1997
Nov 7, 1996
August 7, 1996
June 5, 1996
June 4, 1996
June 3, 1996
Hypertension.” VA Rehab R & D, Atlanta, Georgia.
½ Day Workshop: “Logistic Regression Modeling.” Cleveland Chapter, American Statistical Association.
Invited Seminar: “Design and Statistical Analysis of the African American Study of Kidney Disease and
Hypertension.” Department of Biostatistics, University of Michigan.
Invited Seminar: “Hypothesis Testing for Fixed Effects ANOVA Models with Missing Cells.” Department of
Biostatistics, University of Pennsylvania.
Invited Speaker: “A Unified Regression Approach to Analyzing Fixed Effects ANOVA Models with Missing
Cells.” Cleveland Chapter, American Statistical Association.
Contributed Paper: “A Unified Regression Approach to Analyzing Fixed Effects ANOVA Models with Missing
Cells.” International Biometrics Conference, Cape Town, South Africa.
Invited Speaker: “Linear Regression and Correlation.” Concepts and Methods in Biostatistics, CME Course, The
Cleveland Clinic
Hosted Quantitative Literacy Program. Presented “Overview of the Department of Biostatistics and Epidemiology.”
Contributed Paper: “A Unified Regression Approach to Analyzing Fixed Effects ANOVA Models with Missing
Cells.” International Society for Clinical Biostatistics Conference, Dundee, Scotland.
Invited Seminar: “The Design and Statistical Aspects of the African American Study of Kidney Disease and
Hypertension.” University of Alabama Birmingham, Birmingham, Alabama.
Invited Speaker: “Academic Institution Issues in Industry-Sponsored Clinical Trials.” Drug Information
Association, New Orleans, Louisiana.
Invited Seminar: “A Unified Approach to Analyzing Fixed Effects ANOVA Models.” University of North
Carolina, Chapel Hill, North Carolina.
Invited Seminar: “The Design and Statistical Aspects of the African American Study of Kidney Disease and
Hypertension.” Medical University of South Carolina, Charleston, South Carolina.
Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention,
Atlanta, Georgia (with Ray Greenberg).
Hosted Quantitative Literacy Program. Presented talk: “An Overview of Biostatistics at the Cleveland Clinic”, The
Cleveland Clinic Foundation.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. San Antonio Chapter, ASA, San
Antonio, Texas.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course Central Arkansas Chapter, ASA,
Little Rock, Arkansas.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. South Florida Chapter, ASA, West
Palm Beach, Florida.
Poster Session: “Design and Statistical Aspects of the African American Study of Kidney Diseases and
Hypertension.” Kutner M, Agadoa L, Gassman J, Glassock R, Greene T, Olutade B, Randall O. Twelfth
International Conference on Hypertension in Blacks, London, England.
Invited Speaker: “Linear Regression and Correlation: Concepts and Methods in Biostatistics Course. Cleveland
Clinic Foundation.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. Oregon Chapter, ASA, Portland,
Oregon.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. Sacramento Chapter, ASA,
Sacramento, California.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course. Albuquerque Chapter, ASA,
Albuquerque, New Mexico.
Invited Speaker: “A Unified Approach to Analyzing Data f rom Fixed Effects ANOVA Models.” Department
of Statistics, Los Alamos National Laboratory.
Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention,
Atlanta, Georgia (with Ray Greenberg).
Invited Speaker: “A Unified Approach to Analyzing Data From Fixed Effects ANOVA Models.” Department of
Statistics, University of Florida, Gainesville, Florida.
Invited Talk: “Academe/Industry Collaboration Project.” Industry and Academic Department Heads, Joint
Statistical Meeting, Chicago, Illinois.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course: Central Indiana Chapter, ASA and
University of Indiana School of Medicine, Indianapolis, Indiana.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course: Central Illinois Chapter, ASA
and University of Southern Illinois School of Medicine, Springfield, Illinois.
Invited Speaker: “Logistic Regression Modeling.” ASA Traveling Short Course: Chicago Chapter, ASA, Chicago
Illinois.
Invited Speaker: “Logistic Regression Modeling.” Auburn University and Alabama Chapter, ASA, Auburn,
May 24, 1996
Alabama.
Mar 27-29, 1996 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention,
Atlanta, Georgia (with Ray Greenberg).
Feb 6, 1996
Invited Speaker: “Biostatistics at The Cleveland Clinic Foundation.” Department of Statistics, Brigham Young
University, Provo, Utah.
Nov 29, 1995
Hosted Quantitative Literacy Program. Presented talk: “An Overview of Biostatistics at The Cleveland Clinic.” The
172
Cleveland Clinic Foundation, Cleveland, Ohio.
Invited Speaker: “Biostatistics at the Cleveland Clinic Foundation.” Twelfth Annual Ohio Statistics Conference,
Columbus, Ohio.
Oct 17, 1995
Invited Speaker: “Linear Regression and Correlation: Concepts and Methods in Biostatistics Course.” Cleveland
Clinic Foundation.
Sept 13, 1995
Contributed Paper Session: “Special Care Units for ADRD Residents: Multidimensional Analysis of Outcomes”:
(Presented by Nancy G. Kutner.) XI International Conference, Alzheimer's Disease and Related Disorders,
Buenos Aires, Argentina.
Aug 14, 1995
Invited Speaker: “Biostatistics Training for Established Physicians.” Invited Session sponsored by the Section on
Teaching of Statistics in the Health Sciences, Joint Statistical Meeting, Orlando, Florida.
Jun 26-28, 1995 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention,
Atlanta Georgia. (with Ray Greenberg.)
June 5-7, 1995
Keynote Speaker: “The Use of Diagnostic Tests.” First International Applied Statistics in Medicine Conference
held in conjunction with the Third International Applied Statistics in Industry Conference, Dallas, Texas. Workshop
Presentation: "Principles of Biostatistics in Clinical Research.”
May 5, 1995
Invited Speaker: “A Unified Approach to Analyzing Data f rom Fixed Effects ANOVA Models.” M.D. Anderson
Cancer, Houston, Texas.
May 4, 1995
Invited Speaker: “Biostatistics at the Cleveland Clinic Foundation. Statistics Department, Texas A&M University,
College Station, Texas.
Mar 1-3, 1995
Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention,
Atlanta, Georgia. (with Ray Greenberg.)
Dec 12, 1994
Hosted Quantitative Literacy Program. Presented talk: “An Overview of Biostatistics at The Cleveland Clinic.” The
Cleveland Clinic Foundation, Cleveland, Ohio.
Short Course: “Issues in Regression Analysis Using Statistical Packages.” Societyfor Medical Decision Making,
Oct 16, 1994
Cleveland, Ohio.
Sept 16, 1994
Invited Speaker: “Principles of Biostatistics in Clinical Research.” Gastroenterology Staff and Fellows: Research
Conference, The Cleveland Clinic Foundation, Cleveland, Ohio.
August 16, 1994 Invited Session Discussant: “Short Courses: Challenges, Issues and Educational Value.” 1994 Joint Statistical
Meetings, Toronto, Ontario, Canada.
June 12, 1994
Invited Speaker: “Interpretation of Diagnostic Tests.” Intensive Review of Internal Medicine Course, The Cleveland
Clinic Foundation, Cleveland, Ohio.
Invited Speaker: “Comparing More Than Two Means: Analysis of Variance” and “Linear Regression and
June 6-7, 1994
Correlation.” Biostatistics in Medicine Course, The Cleveland Clinic Foundation, Cleveland, Ohio.
June 1, 1994
Invited Speaker: “Some Interesting Regression Modeling Examples.” Cleveland Chapter, American Statistical
Association, Cleveland, Ohio.
April 26, 1994
Invited Speaker: “Estimating and Testing in ANOVA Models with Some Empty Cells (Eisenhart Model I).” Ohio
State University, Department of Statistics, Columbus, Ohio
April 21, 1994
Invited Speaker: “Estimating and Testing in ANOVA Models with Some Empty Cells (Eisenhart Model I).”
Cincinnati Chapter, American Statistical Association and Department of Mathematics and Statistics, Miami University,
Oxford, Ohio.
Mar 14-16, 1994 Short Course: “Regression Modeling for Epidemiologic Research.” National Institute for Occupational Safety
and Health, Cincinnati, Ohio. (with Ray Greenberg.)
March 9-11, 1994 Short Course: “Regression Modeling for Epidemiologic Research.” Centers for Disease Control and Prevention,
Atlanta, Georgia. (with Ray Greenberg.)
January 19, 1994 Presented Departmental Overview to Northeast Ohio Quantitative Literacy Program, The Cleveland Clinic
Foundation, Cleveland, Ohio.
Sept 12-14, 1993 Research Institute Retreat: “Outliers and Their Effects,” Salt Fork State Park, Ohio.
April 10, 1992
Seminar: “Interpretation of Survival in Clinical Trials.” Pediatric Allergy Journal Club.
Nov 1991
Seminar: “Common Methods of Analyzing Response Data in Clinical Trials.” Pediatric Allergy Journal Club.
Aug 18-23, 1991 Short Courses: “Advanced Multivariate Methods.” International Course in Epidemiology and Research
Methodology, Vouliagmeni Beach, Greece. (with Ray Greenberg.)
April 1991
Journal Club Speaker. “Diagnostic Tests: An Introduction to Probability.” Department of Pediatrics.
Oct 5-6, 1990
Invited Speaker: “Statistical Applications in the Medical and Health Services Field.” John Neter Recognition
Weekend. Athens, Georgia.
July 16-27, 1990 “EPI 732: Statistical Methods.” The University of Michigan Graduate Summer Session in Epidemiology. (With
Ray Greenberg.)
April 5, 1990
Invited Speaker: “ANOVA Models with Empty Cells.” Virginia Polytechnic Institute and State University.
Mar 1990-June 1991
Series of monthly biostatistics seminars to fellows and faculty in Division of Pediatric Hematology/Oncology.
Jan 8-16, 1990
Indo-U.S. Workshop: “Biostatistics and Epidemiological Methods in Ophthalmology.” New Delhi, India.
Oct 11, 1989
Seminar: “Outliers.” Clinical Research Center.
1989
Panel Discussant: “Statistics Programs in Georgia.” Atlanta Chapter, American Statistical Association.
July 18-23, 1988 “Cross-classified Fixed Effects ANOVA Models with Missing Cells.” XIVth International Biometric Conference.
Namur, Belgium.
December 1987 “ANOVA Models in the Case of Missing Cells.” Atlanta Chapter, American Statistical Association.
Jan 3-5, 1987
“A Unified Approach to the Analysis of Balanced and Unbalanced Fixed Effects Data.” American Statistical
Nov 16, 1995
173
Association Winter Conference.
Series of Ten Week Short Courses (2 hours/week): “Regression Modeling in Epidemiologic Research.” Centers for
Disease Control.
Sept.-Nov. 1985 Ten Week Short Course (2 hours/week): “Mathematical Modeling in Epidemiologic Research: Logistic
Regression.” Centers for Disease Control.
Aug 5-8, 1985
“Graduate Service Statistics Courses: What, to Whom and by Whom?” Annual Meeting of the American Statistical
Association. Las Vegas, Nevada.
April 25, 1985
Seminar: “Prediction and Normal Limits in Clinical Research.” The Atlanta Cancer Surveillance Center.
1984
Ten Week Short Course (2 hours/week): “Multivariable Statistical Techniques: Principles and Applications.”
Centers for Disease Control.
June 13, 1984
Seminar: “Biometrical Considerations in Designing a Clinical Study.” Clinical Research Center.
May 1984
Tutorial on Unbalanced Analysis of Variance. Special Colloquium. University of Georgia.
May 24, 1982
“Nonlinear Regression: A Tutorial.” Atlanta Chapter, American Statistical Association.
Nov 1-6, 1981
“Experimental Designs in Rehabilitation Research.” Course Organizer and Presenter. American Congress of
Rehabilitation Medicine Meeting. San Diego, California.
Aug 10-13, 1981 “Using a University-Based Clinical Research Facility to Train Statistics Graduate Students in Statistical
Consultation.” Invited paper, Annual ASA Meeting. Detroit, Michigan.
1986 – 1992
1980
Nov 14, 1979
Georgia.
1978
1978
1978
March 1978
November 1977
Apr 14-15, 1977
Mar 8-10, 1976
March 20, 1975
1974
Aug 26-29, 1974
April 6, 1974
October 1973
Aug 14-17, 1972
Jun 11-16, 1972
February 1971
Dec 27-30, 1970
May 1962
“Single Subject Designs and Group Comparison Designs.” Designs for Rehabilitation Research Conference.
Atlanta, Georgia.
Seminar: “The Significance of Significance Testing.” Clinical Research Center, Emory University, Atlanta,
Seminar: “Analysis of Time Series Data.” Centers for Disease Control, Atlanta, Georgia.
Seminar: “Analysis of Variance and Covariance.” Centers for Disease Control, Atlanta, Georgia.
“Periodic Regression Analysis: A Demographic Model Building Technique.” Annual Population Association of
American Meeting. Atlanta, Georgia.
“Seasonal Variation in Fertility Using Periodic Regression Analysis.” Annual Southern Sociological Society
Meeting. New Orleans, Louisiana. (With C.W. Warren, R.P. Briggs and C.W. Tyler.)
“The Analysis of Multiple Variable Dependencies in Chronic Disease Etiology.” Invited paper, American Public
Health Association Meeting. Washington, D.C. (With B.A. Blumenstein.)
“Analysis of Variance Incorporating Trend Analysis with Unbalanced Data.” Tenth Annual Symposium on the
Interface of Computer Science and Statistics. National Bureau of Standards.
“Path Analysis: Some Biometrical Examples.” Regional Biometrics Meeting. College Station, Texas. (With B.A.
Blumenstein.)
Seminar: “Variance Component Estimation.” Concordia University. Montreal, Canada.
Seminar: “Nonorthogonal Data Analysis.” Kansas State University.
“Hypothesis Testing in Unbalanced Crossed Classified Fixed Effects Models.” Annual ASA Meeting. St. Louis,
Missouri.
Dinner Speaker. Atlanta Chapter ASA Meeting.
“A Critique: Hair Sulfur Analysis for Evaluation of Normal and Abnormal Hair.” First Human Hair Symposium,
Atlanta, Georgia.
“Comparative Studies of Variance Components for the Balanced Incomplete Block Design Under an Eisenhart
Model II.” Annual ASA Meeting. Montreal, Canada.
“Maximum Likelihood Analysis of Mixed Linear Models: The Balanced Incomplete Block Model.” SREB
Summer Research Conference in Statistics. Mountain Lake, Virginia.
“Estimation of Variance Components Via Maximum Likelihood.” Emory University. Atlanta, Georgia.
“Quasi-Maximum Likelihood Estimates of Variance Components.” The Allied Social Science Association Meeting.
Detroit, Michigan.
“A Statistical Analysis of a Crop Rotation Experiment.” Virginia Academy of Sciences Meeting.
MEMBERSHIP IN PROFESSIONAL ORGANIZATIONS
American Statistical Association (Member since 1962)
2013-2015
2015
2003 – 2008
2001
2000 - 2001
1998 - 2000
1994
1994
1993 - 1995
1990 - 1991
Appointed to Dixon Awards Committee, American Statistical Association
Chair, W.J. Dixon Awards Committee, American Statistical Association
Member, Finance Committee
Chair, Local Assistance Committee, Joint Statistical Meeting
Nomination Committee Member (President and Vice President)
Elected Council of Sections Representative, Section on Statistical Consulting
Joint Program Committee: Section on Teaching of Statistics in the Health Sciences
Organized, Chaired and Discussed Invited Paper Session Joint Statistical Meetings
Board Member, District Representative
Member, Local Arrangements Committee, Joint Statistical Meetings
174
1988-1990
1988
1988-1989
1987-1989
1987-1994
1987
1985-1986
1984-1986:
1985-1986
1984-1986
1981-1983
1981-1983
1983
1980
1978-1980
1979-1982
1979-1982
1977-1978
1975-1976
1975
1974
1975; 1977-80
1977-1979
1974-1976
1973-1974
1972-1973
Member, Publications Committee, Vice-Chair
Member, Ad Hoc Committee on Transition Costs for Editors of ASA Publications
Committee on the ASA Sesquicentennial; Chair of Finance Subcommittee
Winter Conference Evaluator Institutional
Membership Representative Winter
Conference Coordinator
Chair, Nominating Committee for District Governor Chair of Council of Governors and ASA Board
Representative
Member, Ad Hoc Committee on ASA Policy on Grants and Contracts
Executive Committee, Council of Chapters, District 5 Governor
President, Atlanta Chapter ASA
Board Member, District 5 Representative
Member, Budget Committee of Board
Chair, Budget Committee of Board
Organized and Chaired, Invited Session at National ASA Meeting
Associate Editor, The American Statistician
Vice-Chair, Ad Hoc Committee of Sections and Subsections
Vice Chair, Committee to Revise the ASA Constitution
Member, Ad Hoc Committee on Chapters Outside U.S. and Canada
Member, Ad Hoc Committee on Membership, Dues and Publications
Vice-Chair, Executive Committee of Local Arrangements National ASA Meeting
Chair, Nominating Committee for District 5 Representative
Chair, Nominating Committee, Atlanta Chapter ASA
Chair, Committee on Chapter, District and Regional Activities
Member, Committee on Chapter, District and Regional Activities
President, Atlanta Chapter ASA
Secretary/Vice President, Atlanta Chapter ASA
American Statistical Association Elected Office
American Statistical Association - Board of Directors, 1981-1983, 1993-1995
Management Review Committee Member
Board Planning Teams: Outreach, Chair; Activities for non-Ph.D. members
Council of Chapters Governing Board: Chair, Fellows Committee
Biometrics Society (Member since 1971)
2010, Chaired IMS Special Lecture Session
1994, Served on Local Arrangements Committee for the Biometrics Spring Meeting, Eastern North American Region,
Cleveland, Ohio
1986, Local Arrangements Chair, 1986 Regional Meeting (ENAR)
1981-1983, Member, Regional Advisory Board (ENAR)
Virginia Academy of Sciences (Member 1960-1967)
1966-1967
Vice President, Statistics Section
Southern Regional Council on Statistics (Member 1986-1993; 2000-)
2012
Local Arrangements Chair, Jekyll Island, Georgia
2010-2011
Past-President and Member of Program Committee for 2011 SRC
2009
Co-Program Chair, Summer Research Conference, Jekyll Island, Georgia
2008-2009
President
2006-2007
President-Elect
1992-1994
Executive Committee, Secretary
1988-1990
Member, Summer Research Conference Planning Committee
1989
Program Chair, Summer Research Conference
1989-1993
Chair, Awards Committee
1986-1993
Institutional Representative
Society for Clinical Trials (Member since 1994)
th
2009 Invited Session Organized and Speaker at Annual Meeting, May 4
2004 Organized and Chaired Invited Session at Annual Meeting, May 26th
2004 Program Committee
175
CONSULTING AND/OR ADVISING
2011-2014
St. Jude Medical
2008-2009
Eagle Pharmaceuticals
1993-1995
Scientific Review Committee, American Cancer Society - "Colon Polyp Prevention Study"
1992-1993
Chief Statistician, Statistical Protocol Review Group, National Institute for Occupational Safety and
Health
1991-1994
CytRx Corporation
1991-1994
Theragenics Corporation
1991-1994
Porex Pharmaceuticals
1990-1994
Solvay Pharmaceuticals
1990-1995
Technical Advisory Committee, American Cancer Society – “A Clinical Study of a Calorie
Controlled/Low Fat Diet in Prevention of Breast Cancer Recurrence”
1990-1991
Bard Urological
1989-1990
Norwich-Eaton Pharmaceuticals
1986-1989
Labthermics Technologies, Inc.
1983
Middle South Utilities
1983-1987
Veterans Administration, Operations Committee Member
1980
DeKalb County School System
1979-1980
Mary Ann Oakley, Attorney (Age Discrimination Case)
1974Centers for Disease Control and Prevention
1976-1980
Georgia Power Company (Environmental Studies Division)
1976
National Heart and Lung Institute
REFEREEING (STATISTICAL JOURNALS)
Journal of the American Statistical Association, The American Statistician, Biometrics, Technometrics, Communications in Statistics, Journal
of Statistical Computation and Simulation, Journal of Official Statistics
JOURNAL EDITORSHIP
Statistical Editor, Annals of Epidemiology (2003-2008)
OUTSIDE PROFESSIONAL ACTIVITIES
Data and Safety Monitoring Boards
• Member, Data and Safety Monitoring Committee, Winship Cancer Institute, 2011-present
• Member, Data and Safety Monitoring Committee for NIDDK U01 grant: “Treatment of Chronic Disease
Mineral Bone Disorder”
• Home-Based AIDS Core Project, Chair, DSMB, Uganda/CDC
• Multicenter Selective Lymphadenectomy Trial (MSLT) funded by the National Cancer Institute
• HALT-C Trial funded by National Institute of Diabetes, Digestive and Kidney Diseases
• Chair, Data Safety Monitoring Committee, “A Peer-led, Medical Disease Self-management Program for Mental
Health Consumers” (PI: B. Druss)
Advisory Committees/Special NIH Panel Reviewer
• Special Reviewer NIH/NCI Grants
• Special Reviewer NIH/NIAID Training Grants
• Alumni Advisory Committee, Texas A & M, Department of Statistics
• Advisory Committee, Lung Cancer SCORE Grant, Winship Cancer Institute
• Advisory Committee, Exploratory Nursing Research Center, Emory University School of Nursing
• Dialysis Outcomes and Practice Patterns Study Advisory Board Member, AMGEN.
• Advisory Board, Department of Mathematical Sciences, Clemson University
• Review Biostatistics and Bioinformatics Programs, Northwestern University School of Medicine
GRANT SUPPORT (2011-2014)
•
•
5 P30 AI50409-15 (Curran), 08/01/98-01/01/15
0.60 calendar months
NIH $1,357,566, Centers for AIDS Research
3P01CA116676-05S1 (Khuri), 06/20/06-05/31/12
0.24 calendar months
NIH $4,420,995, Targeting Cell Signaling in Lung Cancer to Enhance Therapeutic Efficacy
176
•
•
•
•
•
•
•
•
5 P50 MH077083-04 (Mayberg), 07/14/06-06/30/11
0.60 calendar months
NIH $1,202,123, Predictors of Antidepressant Treatment Response: The Emory Cidar
5 P01 HD32571-19 (English), 04/20/95-03/31/17
0.60 calendar months
NIH/NICHD $3,402,250, Spinal Circuits and the Musculoskeletal System
5 P50 MH077928-04 (Stowe), 09/01/07-07/31/12
0.60 calendar months
NIH/NIMH $4,098,570, Perinatal Stress and Gene Influences: Pathways to Infant Vulnerability
5 P01 HL086773-03 (Roback), 07/01/08-08/31/13
0.96 calendar months
NIH $1,249,686, Mechanisms and Interventions Addressing Serious Hazards of Transfusion and Cellular
Therapies
0.60 calendar months
5 R21 AT004220-02 (Kutner), 07/01/09-06/30/12
NIH $152,756, Melatonin Supplementation and the Metabolic Syndrome
3 R21 AT00450901-A2S1 (Abramson), 09/30/09-09/29/11
0.48 calendar months
NIH $162,875, Melatonin and Nighttime Blood Pressure in African Americans
1 R34 AI091437-01 (Omer), 09/23/10-08/31/12
0.36 calendar months
NIH $174,916, Effects of Maternal Influenza Immunization: A Field Trial in Guatemala
1 P01 HL101398-01 (Sheps), 09/01/10-05/31/15
0.60 calendar months
NIH/NHLBI $1,425,790, Mental Stress Ischemia: Mechanisms and Prognosis
177
JEFFREY S. MORRIS
Department of Biostatistics, University of Texas M.D. Anderson Cancer Center
P.O. Box 301402, Houston, Texas 77230-1402
Voice: 713-563-4284 Email: [email protected]
EDUCATION
Ph.D., Statistics, Texas A&M University, August 2000. Advisors: Raymond J. Carroll and Naisyin Wang
M.S., Statistics, Texas A&M University, December 1997.
B.S., Mathematics Education, Messiah College, May 1993.
PROFESSIONAL EXPERIENCE
- February 2011-: Deputy Chair, Department of Biostatistics, University of Texas MD Anderson Cancer Center
- September 2010- : Professor, Department of Biostatistics, University of Texas MD Anderson Cancer Center
- August 2010-February 2011: Long Term Visiting Fellow, Statistical and Applied Mathematical Sciences Institute
(SAMSI), Analysis of Object Data
- September 2005-August 2010: Associate Professor, Department of Biostatistics, University of Texas MD
Anderson Cancer Center.
- May 2001-July 2001: Visiting Fellow, University of Kent at Canterbury.
- August 2000-August 2005: Assistant Professor, Department of Biostatistics, University of Texas MD Anderson
Cancer Center.
- June 1998-August 2000: Research Assistant, Texas A&M University.
- January 1998-May 1998: Assistant Lecturer, Texas A&M University.
- May 1997-July 1997: Intern, Hoechst Marion Roussel, Kansas City, MO.
- August 1995-December 1997: Teaching Assistant, Texas A&M University
- August 1993-August 1995: Teacher, Northside Christian School, St. Petersburg, FL
- January 1993-July 1993: Computer Programmer, IBM, Mechanicsburg, PA.
HONORS
- Myrto Lefkopoulou Distinguished Lectureship, Harvard University, 2011
- Fellow, American Statistical Association, 2011
- H. O. Hartley Award, Texas A&M University Department of Statistics, 2009
- American Statistical Association Noether Young Scholar Award, 2005
- Thomson-ESI Hot Paper in the Field of Computer Science, July 2005
- MD Anderson Cancer Center E.N. Cobb Faculty Scholar Award, 2004
- Best Presentation, 4th Critical Assessment of Microarray Data Analysis, 2003
- Mitchell Prize for Outstanding Bayesian Application Paper, 2003
- JASA Applications and Case Studies Editor’s Invited Paper, 2003
- Best Abstract, 1st Annual Proteomics Data Mining Conference, 2002
- Travel Award for Young Researchers, Biometrics Section of ASA, 2001
- Texas A&M College of Science Dean’s Graduate Fellowship, 1995
- Texas A&M University Graduate Merit Fellowship, 1995
RESEARCH GRANTS AND CONTRACTS
Current:
• National Cancer Institute, (CA-096520), T32, Training Program in Biostatistics for Cancer Research, Funded
Through 2018. (Co-PI, Marina Vannucci PI).
• National Cancer Institute, (CA-160736), R01, Integrative Methods for High-Dimensional Genomics Data,
Funded through 2015. (Co-PI, Veera Baladandayuthapani PI).
• National Cancer Institute (CA-016672), P30, Cancer Center Support Grant, 2000-present (Statistician, Ron
DePinho PI). Funded through 2018.
• National Institute on Drug Abuse (DA-032581), R01, Beyond Cue Reactivity: ERPs,Sensitivity to Natural
Rewards, and Smoking Cessation, Funded through 2015. (Co-Investigator, Francesco Versace PI).
• National Cancer Institute, (CA-137213), R01, 15-LOX-1 effects on colitis and colon cancer, Funded through
2011. (Statistician, Imad Shureiqi PI).
• National Cancer Institute, (CA-142969), R01, Molecular targeting of PPAR-delta in colon cancer, funded through
2015. (Co-Investigator, Imad Shureiqi, PI)
178
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
National Cancer Institute, (CA-130821), P01, Cellular and Molecular Mechanisms of Gastrointestinal Cancers,
Funded through 2014. (Co-Investigator, Lopa Misra PI).
National Cancer Institute, (CA-158676), R21, Determinants of Efficacy to the Akt Inhibitor Perifosine in
Metastatic Colorectal Cancer, Funded through 2013. (Statistician, Cathy Eng PI).
National Cancer Institute, (CA-045809), U10, UT MD Anderson Cancer Center Community Clinical Oncology
Research Base, Funded through 2017. (Biostatistics Core Director, Michael Fisch PI).
National Cancer Institute, (CA172670), R01, Stress Signaling Pathways and Resistance in Colorectal Cancer,
Funded through 2017 (Co-Investigator, Scott Kopetz PI).
National Cancer Institute, (CA170035), R21, Integrating plasma IGF-1 into novel classification of hepatocellular
carcinoma, Funded through 2014. (Co-Investigator, Ahmed Kaseb PI)
Cancer Prevention & Research Institute of Texas (CPRIT), (RP101207), P04, CERCIT: Comparative
Effectiveness Research of Cancer in Texas, Funded through 2013 (Collaborator, Linda Elting PI).
National Institute on Minority Health and Health Disparities, (MD-007056), R01, Environmental and Genetic
Factors for Pancreatic Cancer Among Blacks, Funded through 2017. (Statistician, Donghui Li, PI)
Completed:
National Cancer Institute (CA-107304), R01, Adaptive Methods for Biomedical Functional Data, 2004-2013 (PI).
National Cancer Institute (CA-098380), R01, Molecular Epidemiology of Pancreatic Cancer, 2004-2011
(Statistician, Donghui Li PI).
National Cancer Institute, (CA-136980), K23, SrC Inhibition in Colorectal Cancer, Funded through 2013.
(Statistician, Scott Kopetz PI).
National Cancer Institute, (CA-142969), R01, Molecular Targeting of PPAR-delta in colon cancer, (Statistician,
Imad Shureiqi, PI), Funded through 2011.
National Institute for Alcohol Abuse (AA-016157), R01, Brain Biomarkers of Alcoholism and Abstinence, 20062011 (co-PI, Howard Gutstein PI).
National Institute on Drug Abuse (DA-0154604), R01, From Drug Use to Addiction: Unearthing the Switches,
2002-2007 (Collaborator, Howard Gutstein PI).
National Institute for Alcohol Abuse (AA-1388602), R56, Proteomic Approaches to Alcoholism, 2005-2008
(Collaborator, Howard Gutstein PI).
National Cancer Institute (CN-005126), N01, A Phase I/II Study of Celecoxib in Genotype-Positive, PhenotypeNegative Children with FAR, 2000-2007 (Statistician, Patrick Lynch PI).
American Cancer Society (RSG-04-020-01-CNE), 15-Lipoxygenase-1 and Mechanisms of Colorectal
Tumorigenesis, 2004-2007 (Statistician, Imad Shureiqi PI).
National Cancer Institute (CA-104278), R01, Molecular Targeting of 15-Lipoxygenase-1 Colon Cancer, 2004-2008
(Statistician, Imad Shureiqi PI)
National Cancer Institute (CA-106577), R01, 5-LOX-1 and Clinical Chemoprevention of Colon Tumors
(Collaborator, Imad Shureiqi PI). 2005-2009.
National Cancer Institute (CA-139767), R13, Conference on “Statistical Methods for Complex Biological Data”,
2009-2010 (PI).
Patents:
1. Morris JS and Gutstein H, inventors: Method and Computer-Program Product for Detecting and Quantifying
Protein Spots, Patent Number US 8,031,925, Issue Date 10/4/2011.
PUBLICATIONS (Note: * indicates corresponding or joint first/corresponding author)
[1]
Hong MY, Chapkin RS, Wild CP, Morris JS, Wang N, Carroll RJ, Turner ND and Lupton JR (1999). Relationship
Between DNA Adduct Levels, Repair Enzyme and Apoptosis as a Function of DNA Alkylation by
Azoxymethane. Cell Growth and Differentiation, 10: 749-758.
[2]
Hong MY, Lupton JR, Morris JS, Wang N, Carroll RJ, Davidson LA, Elder R and Chapkin RS (2000). Dietary
Fish Oil Reduces 06-methylguanine DNA Adduct Levels in the Rat Colon In Part By Increasing Apoptosis
During Tumor Initiation. Cancer Epidemiology, Biomarkers and Prevention, 9: 819-826.
[3]
Davidson LA, Brown RE, Chang W-CL, Lupton JR, Morris JS, Wang N, Carroll, RJ, Turner, ND and Chapkin,
RS (2000). Morphodensitometric Analysis of Protein Kinase C II Expression in the Rat Colon: Modulation by
Diet and Relation to in situ Cell Proliferation and Apoptosis. Carcinogenesis, 21: 1513-1519.
[4]
Rashid A, Lanlan S, Morris JS, Issa J-PJ, Hamilton SR (2001). CpG island methylation in colorectal adenomas.
The American Journal of Pathology, 159:1129-1135.
[5]
Morris JS, Wang N, Lupton JR, Chapkin RS, Turner ND, Hong MY and Carroll RJ (2001). Parametric and
Nonparametric Methods for Understanding the Relationship Between Carcinogen-Induced DNA Adduct Levels
in Distal and Proximal Regions of the Colon. Journal of the American Statistical Association, 96: 816-826.
179
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
[26]
[27]
[28]
Shureiqi I, Cook CD, Morris JS, Soliman AS, Levin B, and Lippman SM (2001). Effect of Age on Risk of Second
Primary Colorectal Cancer. Journal of the National Cancer Institute, 93: 1264-1265.
Hong MY, Chapkin RS, Morris JS, Wang N, Carroll RJ, Turner ND, Chang WCL, Davidson FA and Lupton JR
(2001). Anatomical Site-Specific Response to DNA Damage is Related to Later Tumor Development in the Rat
AOM Colon Carcinogenesis Model. Carcinogenesis, 22:1831-1835.
Arrington JL, Chapkin RS, Switzer KC, Morris JS and McMurray DN (2001). Dietary n-3 Polyunsaturated Fatty
Acids Modulate Purified Murine T-cell Subset Activation. Clinical and Experimental Immunology, 125: 499-507.
Shureiqi I, Xu X, Chen D, Lotan R, Morris JS, Fischer SM and Lippman SM (2001). Nonsteroidal Antiinflammatory Drugs Induce Apoptosis in Esophageal Cancer Cells by Restoring 15-Lipoxygenase-1 Expression.
Cancer Research 61: 4879-4884.
Chan AOO, Issa-J-PJ, Morris JS, Hamilton SR and Rashid A: Concordant CpG Island Methylation in
Hyperplastic Polyposis (2002). The American Journal of Pathology, 160: 529-536. PMID: 11839573. PMCID:
PMC1850645.
Morris JS (2002). The BLUPs Are Not “Best” When It Comes To Bootstrapping. Statistics and Probability
Letters, 56: 425-430.
Morris JS, Wang N, Lupton JR, Chapkin RS, Turner ND, Hong MY and Carroll RJ (2002). A Bayesian Analysis
Involving Colonic Crypt Structure and Coordinated Response to Carcinogens Incorporating Missing Crypts,
Biostatistics, 3: 529-546.
Baggerly K, Deng L, Morris JS, Aldez CM (2003). Differential expression in SAGE: Accounting for normal
between-library variation. Bioinformatics, 19(12): 1477-1483.
Baggerly K, Morris JS, Wang J, Gold D, Xiao LC and Coombes K (2003). A comprehensive approach to the
analysis of MALDI-TOF proteomics spectra from serum samples. Proteomics, 3: 1667-1672 (Won Best
Presentation at 2002 Duke University Proteomics Data Mining Competition).
Morris JS, Baggerly K, and Coombes K (2003). Bayesian Shrinkage Estimators of the Relative Abundance of
mRNA Transcripts using SAGE. Biometrics, 59: 476-486.
Morris JS, Vannucci M, Brown PJ and Carroll RJ (2003). Wavelet-Based Nonparametric Modeling of Hierarchical
Functions in Colon Carcinogenesis [with discussion]. Journal of the American Statistical Association, 98: 573-583
(Editor’s Invited Paper and chosen to receive Mitchell Prize).
Coombes KR, Fritsche HA Jr., Clarke C, Cheng JN, Baggerly KA, Morris JS, Xiao LC, Hung MC, and Kuerer
HM (2003). Quality Control and Peak Finding for Proteomics Data Collected from Nipple Aspirate Fluid Using
Surface Enhanced Laser Desorption and Ionization. Clinical Chemistry, 49(10): 1615-1623.
Morris JS, Wang N, Lupton JR, Chapkin RS, Turner ND, Hong MY, and Carroll RJ (2003). Understanding the
Relationship between Carcinogen-induced DNA Adduct Levels in Distal and Proximal Regions of the Colon.
Advances in Experimental Medicine and Biology, 537: 105-116.
Lin E, Morris JS, and Ayers GD (2003). Effect of Celecoxib on capecitabine-induced hand-foot syndrome and
antitumor activity. Oncology, 16 (12 supplement No 14): 31-37.
Madoff DC, Hicks ME, Abdalla EK, Morris JS and Vauthey JN (2003). Portal vein embolization using polyvinyl
alcohol particles and coils in preparation for major liver resection for hepatobiliary malignancy: Safety and
Efficacy: A study in 26 patients. Radiology, 227(1): 251-260.
Shureiqi I, Jiang W, Zuo X, Wu Y, Stimmel JB, Leesnitzer LM, Morris JS, Fan HZ, Fischer SM, Lippman SM
(2003). The 15-lipoxygenase-1 product 13-S-hydroxyocta-decadienoic acid down-regulates PPAR-{delta} to
induce apoptosis in colorectal cancer cells. Proceedings of the National Academy of Sciences, 100(17): 9968-9973.
PMID: 12909723. PMCID: PMC187904.
Pawlik TM, Paulino AF, Mcginn CJ, Baker LH, Cohen DS, Morris JS, Rees R, and Sondak VK (2003). Cutaneous
angiosarcoma of the scalp: A multidisciplinary approach. Cancer, 98(8): 1716-1726.
Pawlik TM, Izzo F, Cohen DS, Morris JS, and Curley SA (2003). Combined resection and radiofrequency ablation
for advanced hepatic malignancies: Results in 172 patients. Journal of Surgical Oncology, 10(9): 1059-1069.
Baggerly, KA, Morris JS, and Coombes KR (2004). Reproducibility of SELDI Mass Spectrometry Patterns in
Serum: Comparing Proteomic Data Sets from Different Experiments. Bioinformatics, 20(5): 777-785 (Identified
by Thomson-ISI as “one of the most cited recent papers in the field of computer science”,see http://www.esitopics.com/nhp/2005/july-05-KeithBaggerly.html).
Baggerly KA, Edmonson S, Morris JS, and Coombes KR (2004). High-Resolution Serum Proteomic Patterns for
Ovarian Cancer Detection. Endocrine-Related Cancers, 11(4): 583-584.
Baggerly KA, Deng L, Morris JS, and Aldez CM (2004). Overdispersed Logistic Regression for SAGE: Modeling
Multiple Groups and Covariates. BMC Bioinformatics, 5:144. PMID: 1569612. PMCID: PMC524524.
Marron JS, Muller HG, Rice J, Wang JL, Wang N, Wang Y, Coull B, Fahrmeier L, Guo W, Hall P, Harezlak J,
Huang J, Kneip A, Lin X, Morris JS, Pourmadi M, Staudenmayer J, Wu C, Zhang D, Zhang H, and Zhao Y
(2004). Discussion of nonparametric and semiparametric regression. Statistica Sinica 14(3): 615-621.
Sinicrope FA, Half E., Morris JS, Lynch PM, Morrow JD, Levin B, Steinbach G, Hawk ET, Cohen DS, Ayers
GD, Stephens LC, FAP Study Group (2004). Cell proliferation and apoptotic indices predict adenoma regression
180
[29]
[30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
[39]
[40]
[41]
[42]
[43]
[44]
[45]
[46]
[47]
in a placebo-controlled trial of celecoxib in Familial Adenomatous Polyposis (FAP) patients. Cancer
Epidemiology, Biomarkers, and Prevention, 13(6): 1-8.
Ajani J, Walsch G, Komaki RR, Morris JS, Swisher SG, Lynch P, Wu TT, Vaporciyan A, Faust JC, Nivers RJ, and
Roth J (2004). Preoperative induction CPT-11 and cisplatin chemotherapy followed by chemoradiotherapy in
patients with local-regional carcinoma of the esophagus or gastroesophageal junction. Cancer, 100(11): 23472354.
Kalha I, Kaw M, Fukami N, Patel M, Singh S, Gagneja H, Cohen D, Morris JS (2004). The accuracy of
endoscopic ultrasound for restaging esophageal carcinoma after chemoradiation therapy. Cancer, 101(5): 940-947.
PMID: 15329901.
Ajani JA, Mansfield PF, Janjan N, Morris JS, Pisters PW, Lynch PM, Feig B, Myerson R, Nivers R, Cohen DS,
and Gunderson LL (2004). A multi-institutional trial of preoperative chemoradiotherapy in patients with
potentially resectable gastric carcinoma. Journal of Clinical Oncology, 22(14), 2774-2780.
Baggerly KA, Morris JS, Edmonson S, and Coombes KR (2005). Signal in Noise: Evaluating Reported
Reproducibility of Serum Proteomic Tests for Ovarian Cancer. Journal of the National Cancer Institute, 97: 307309, (with commentary).
Morris JS, Coombes KR, Kooman J, Baggerly KA, and Kobayashi R (2005). Feature Extraction and
Quantification for Mass Spectrometry Data in Biomedical Applications Using the Mean Spectrum. Bioinformatics,
21(9): 1764-1775.
Coombes KR, Morris JS, Hu J, Edmondson SR, and Baggerly KA (2005). Serum Proteomics Profiling: A Young
Technology Begins to Mature. Nature Biotechnology, 23(3): 291-292. PMID: 15765078.
Hu J, Coombes KR, Morris JS, and Baggerly KA (2005). The Importance of Experimental Design in Proteomic
Mass Spectrometry Experiments: Some Cautionary Tales. Briefings in Genomics and Proteomics, 3(4), 322-331.
Coombes KR, Tsavachidis S, Morris JS, Baggerly KA, and Kuerer HM (2005). Improved Peak Detection and
Quantification of Mass Spectrometry Data Acquired from Surface-Enhanced Laser Desorption and Ionization by
Denoising Spectra with the Undecimated Discrete Wavelet Transform. Proteomics, 5: 4107-4117. PMID:
16254928.
Baggerly KA, Coombes KR, and Morris JS (2005). Bias, Randomization, and Ovarian Proteomic Data: A Reply
to Producers and Consumers. Cancer Informatics, 1(1): 9-14. PMID: 19305627. PMCID: PMC26527654.
Coombes KR, Koomen, JM, Baggerly KA, Morris JS, and Kobayashi R (2005). Understanding the characteristics
of mass spectrometry data through the use of simulation. Cancer Informatics, 1(1): 41-52. PMID: 19305631.
PMCID: 2657656.
Madoff DC, Abdalla EK, Gupta S, Wu TT, Morris JS, Denys A, Wallace MJ, Morello FA Jr, Ahrar K, Murthy R,
Lunagomez S, Hicks ME, Vauthey JN (2005). Transhepatic ipsilateral right portal vein embolization extended to
segment IV: improving hypertrophy and resection outcomes with spherical particles and coils. Journal of
Vascular and Interventional Radiology, 2(1): 215-225.
Ajani JA, Mansfield PF, Crane CH, Wu TT, Lunagomez S, Lynch PM, Janjan N, Feig B, Faust J, Yao JC, Nivers
R, Morris JS, and Pisters PW (2005). Paclitaxel-based chemoradiotherapy in localized gastric carcinoma: Degree
of pathologic response and not clinical parameters dictated patient outcome. Journal of Clinical Oncology, 23(6),
1237-1244.
Hu, J, Yin G, Morris JS, Zhang L, and Wright FA (2005). Entropy and Survival-based Weights to Combine
Affymetrix Array Types in the Analysis of Differential Expression and Survival. Methods of Microarray Data
Analysis IV, eds. JS Shoemaker and SM Lin, pp. 95-108, New York: Springer-Verlag.
Morris JS, Yin G, Baggerly KA, Wu C, and Zhang L (2005). Pooling Information Across Different Studies and
Oligonucleotide Microarray Chip Types to Identify Prognostic Genes for Lung Cancer. Methods of Microarray
Data Analysis IV, eds. JS Shoemaker and SM Lin, pp. 51-66, New York: Springer-Verlag, 2005 (Won best
presentation at CAMDA 2003 meetings).
Chirieac LR, Swisher SG, Ajani JA, Komaki RR, Correa AM, Morris JS, Roth JA, Rashid A, Hamilton SR, and Wu
TT (2005). Posttherapy pathological stage predicts survival in patients with esophageal carcinoma receiving
preoperative chemoradiation. Cancer, 103(7), 1347-1355.
Beach R, Chan AOO, Wu TT, White JA, Morris JS, Lunagomez S, Broaddus RR, Issa JP, Hamilton SR, and
Rashid A (2005). BRAF mutations in aberrant crypt foci and hyperplastic polyposis. The American Journal of
Pathology, 166(4), 1069-1075. PMID: 15793287. PMCID: PMC1602378.
Hong D, Lunagomez S, Kim EE, Lee JH, Bresalier RS, Swisher SG, Wu TT, Morris JS, Liao Z, Komaki R, and
Ajani JA (2005). Value of baseline positron emission tomography for predicting overall survival in patients with
non-metastatic esophageal or gastroesophageal junction carcinoma. Cancer, 104(8): 1620-1626.
Shureiqi I, Wu Y, Chen D, Yang XL, Guan B, Morris JS, Yang P, Newman RA, Broaddus R, Hamilton SR, Lynch
P, Levin B, Fischer SM, and Lippman SM (2005). Critical role of 15-Lipoxygenase-1 in colorectal epithelial cell
terminal differentiation and tumorigenesis. Cancer Research, 65(24): 11486-92. PMID: 16357157. PMCID:
PMC1564070.
Morris JS and Carroll RJ (2006). Wavelet-Based Functional Mixed Models. Journal of the Royal Statistical Society,
Series B, 68(2): 179-199. PMID: 19759841. PMCID: PMC2744105.
181
[48]
[49]
[50]
[51]
[52]
[53]
[54]
[55]
[56]
[57]
[58]
[59]
[60]
[61]
[62]
[63]
[64]
[65]
[66]
[67]
[68]
Morris JS, Arroyo C, Coull B, Ryan LM, Herrick R, and Gortmaker SL (2006). Using Wavelet-Based Functional
Mixed Models to Characterize Population Heterogeneity in Accelerometer Profiles: A Case Study. Journal of the
American Statistical Association, 101(476): 1352-1364. PMID: 19169424. PMCID: PMC2630189.
Mayo MS, Gajewski BJ, and Morris JS (2006): Some Statistical Issues in Microarray Gene Expression Data.
Radiation Research, 165(6): 745-748.
Zuo X, Wu Y, Morris JS, Stimmel JB, Leesnitzer LM, Fischer SM, Lippman SM, Shureiqi I (2006). Oxidative
metabolism of linoleic acid modulates PPAR-beta/delta suppression of PPAR-gamma activity. Oncogene, Feb 23;
25(8):1225-41.
Baggerly KA, Coombes KR, and Morris JS (2006). An Introduction to High-Throughput Bioinformatics Data.
Bayesian Inference for Gene Expression and Proteomics, KA Do, P Mueller, and M Vannucci, eds., Cambridge
University Press, 1-39.
Guindani M, Do KA, Muller P, and Morris JS (2006). Bayesian Mixture Models for Gene Expression and Protein
Profiles. Bayesian Inference for Gene Expression and Proteomics, KA Do, P Mueller, and M Vannucci, eds.,
Cambridge University Press, 238-253.
Morris JS, Baggerly KA, and Coombes KR (2006). Shrinkage Estimation for SAGE Data using a Mixture
Dirichlet Prior. Bayesian Inference for Gene Expression and Proteomics, KA Do, P Mueller, and M Vannucci,
eds., Cambridge University Press, 254-268.
Morris JS, Brown PJ, Baggerly KA, and Coombes KR (2006). Analysis of Mass Spectrometry Data Using Bayesian
Wavelet-Based Functional Mixed Models. Bayesian Inference for Gene Expression and Proteomics, KA Do, P
Mueller, and M Vannucci, eds., Cambridge University Press, 269-292.
Rohatgi PR, Mansfield PF, Crane CH, Wu TT, Sunder PK, Ross WA, Morris JS, Pisters PW, Feig BW,
Gunderson LL, and Ajani JA (2006). Surgical pathology stage by The American Joint Commission On Cancer
(AJCC) criteria predicts patient survival after preoperative chemoradiation for localized gastric carcinoma. Cancer,
107(7): 1475-1482.
Krishnan S, Janjan NA, Skibber JM, Rodrigues-Bigas MA, Wolff RA, Das P, DELclos ME, Chang GJ, Hoff PM,
Eng C, Brown TD, Crane CH, Feig BW, Morris JS, Vadhan-Raj S, Hamilton SR, and Lin EH (2006). Phase II
study of capecitabine (Xeloda) and concomitant boost radiotherapy in patients with locally advanced rectal cancer.
Journal of Radiation Oncology, Biology, and Physics, 66(3): 762-771.
Herrick RC, Morris JS (2006). Wavelet-based functional mixed model analysis: Computational Considerations.
Proceedings, Joint Statistical Meetings, ASA Section on Statistical Computing, 2051-2053.
Lin EH, Curley SA, Crane CC, Feig B, Skibber J, Delcos M, Vadhan SR, Morris JS, Ayers GD, Ross A, Brown T,
Rodriguez-Bigas MA, and Janjan N (2006). Retrospective study of capecitabine and celecoxib in metastatic
colorectal cancer: potential benefits and COX-2 as the common mediator in pain, toxicities and survival? Journal
of Clinical Oncology, 29(3): 232-9.
Karpievitch YV, Hill EG, Morris JS, Coombes KR, Baggerly KA and Almeida JS (2007). PrepMs. Bioinformatics
23(2): 264-265. PMID: 17121773. PMCID: PMC2633108.
Song JJ, Lee HJ, Morris JS, and Kang S (2007). Clustering of time-course gene expression data using functional
data analysis. Computational Biology and Chemistry, 31(4), 265-274. PMID: 17631419. PMCID: PMC1992527.
Gutstein HB and Morris JS (2007). Laser capture sampling and analytical issues in proteomics. Expert Reviews in
Proteomics, 4(5), 627-637. PMID: 17941818. PMCID: PMC2639751.
Anandasabapahty S, Jhamb J, Davila M, Wei C, Morris JS, and Bresalier R (2007). Clinical and endoscopic factors
predict higher pathologic grades of Barrett dysplasia. Cancer, 109(4): 558-574.
Cradock AL, Melly SJ, Allen JG, Morris JS, and Gortmaker SL (2007). Characteristics of school campuses and
youth physical activity: Does size matter? American Journal of Preventative Medicine, 33(2): 106-113. PMID:
17673097. PMCID: PMC1992527.
Patel PR, Mansfield PF, Crane CH, Wu TT, Lee JH, Lynch PM, Morris JS, Pisters PW, Feig B, Sunder PK, Izzo
JG, Ajani JA (2007). Clinical stage after preoperative chemoradiation is a better predictor of patient outcome than
the baseline stage for localized gastric cancer. Cancer, 110(5): 989-995.
Coombes, KR, Baggerly KA, and Morris JS (2007). Pre-Processing Mass Spectrometry Data. Fundamentals of
Data Mining in Genomics and Proteomics, W Dubitzky, M Granzow, and D Berrar, eds. Kluwer, Boston, 79-99.
Thomas MB, Chadha R, Glover K, Wang X, Morris JS, Brown T, Rashid A, Dancey J, & Abbruzzesse JL (2007).
A phase II study of Erlotinib (OSI 774) in patients with unresectable hepatocellular carcinoma. Cancer, 110 (5):
1059-1067.
Shureiqi I, Zuo X, Broaddus R, Wu Y, Guan B, Morris JS, and Lippman SM (2007). The transcription factor
GATA-6 is overexpressed in vivo and contributes to silencing 15-LOX-1 in vitro in human colon cancer. FASEB
Journal, 21(3): 743-753. PMID: 17167069. PMCID: PMC1847772.
Chan AOO, Jim MH Lam KF, Morris JS, Siu DCW, Tong T, Ng FH, Wong SY, Hui WM, Chan CK, Lai KC,
Cheung TK, Chan P, Wong G, Yuen MF, Lau YK, Lee S, Szeto ML, Wong BCY, and Lam SK (2007).
Association of colorectal cancer and ademonas in patients with newly diagnosed coronary artery disease: a cross
sectional study. Journal of the American Medical Association, 98(12): 1412-1419. PMID: 17895457.
182
[69]
[70]
[71]
[72]
[73]
[74]
[75]
[76]
[77]
[78]
[79]
[80]
[81]
[82]
[83]
[84]
[85]
[86]
[87]
[88]
[89]
Morris JS, Clark BN and Gutstein HB (2008). Pinnacle: A Fast, Automatic Method for Detecting and Quantifying
Protein Spots in 2-Dimensional Gel Electrophoresis Data. Bioinformatics, 24, 529-536. PMID: 18194961.
PMCID: PMC2662725.
Gutstein HB, Morris JS, Annangudi SP, and Sweedler JV (2008). Microproteomics: Analysis of protein diversity in
small samples. Mass Spectrometry Reviews, 27, 316-330. PMID: 18271009. PMCID: PMC2743962.
Zuo X, Shen L, Issa JP, Moy O, Morris JS, Lippman SM, Shureiqi I (2008). 15-Lipxygenase-1 transcriptional
silencing by DNA methyltransferase-1 independently of DNA methylation. FASEB Journal, 22(6): 1981-92.
PMID: 18198215. PMCID: PMC2410033.
Suehiro Y, Wong CW, Chireac LR, Kondo Y, Shen L, Webb CR, Chan YW, Chan AS, Chan TL, Wu TT, Rashid
A, Hamanaka Y, Hinoda Y, Shannon RL, Wang X, Morris JS, Issa JP, Yuen ST, Leung SY and Hamilton SR
(2008). Epigenetic-genetic interactions in the APC/WNT, RAS/RAF and P53 pathways colorectal carcinoma.
Clinical Cancer Research, 14(9): 2560-2569. PMID: 18451217. PMCID: PMC3544184.
Wu Y, Fang B, Yang XQ, Wang L, Chen D, Krasnykh V, Carter BZ, Morris JS, Shureiqi I (2008). Therapeutic
molecular targeting of 15-Lipoxygenase-1 in colon cancer. Molecular Therapy, 16(5): 886-892. PMID: 18388920.
PMCID: PMC2377397.
Morris JS (2008). Statistical Issues in Proteomic Research. Bulletin of the International Society for Bayesian
Analysis, 14(4), 9-13.
Suzuki H, Morris JS, Li Y, Doll MA, Hein DW, Liu J, Jiao L, Hassan MM, Day RS, Bondy ML, Abbruzzese JL, Li
D (2008). Interaction of the cytochrome P4501A2, SULT1A1 and NAT gene polymorphisms with smoking and
dietary mutagen intake in modification of the risk of pancreatic cancer. Carcinogenesis, 29(6):1184-91. PMID:
18499698, PMCID: PMC2443278.
Overman MJ, Kopetz S, Wen S, Hoff PM, Fogelman D, Morris JS, Abbruzzesse JL, Ajani JA, and Wolff RA
(2008). Chemotherapy with 5-fluorouracil and a platinum compound improves outcomes in metastatic small
bowel adenocarcinoma. Cancer, 2008 Oct 15; 113(8): 2038-45.
Morris JS (2008). Comment on “Sure independence screening for ultra-high dimensional feature space,” by
Jianqing Fan and Jinchi Lv, Journal of the Royal Statistical Society Series B, 70:5, 900-901.
Morris JS, Brown PJ, Herrick RC, Baggerly KA, and Coombes KR (2008). Bayesian Analysis of Mass
Spectrometry Data using Wavelet Based Functional Mixed Models. Biometrics, 12, 479-489. PMID: 17888041.
PMCID: PMC2659628.
Zuo X, Morris JS, and Shureiqi I (2009). Chromatin modification requirements for 15-lipoxygenase-1
transcriptional reactivation in colon cancer cells. J Biol Chem., 283(46): 31341-7. PMID: 18799463. PMCID:
PMC2581547.
Li D, Suzuki H, Liu B, Morris JS, Liu J, Okazaki T, Li Y, Chang P, and Abbruzzese JL (2009). DNA repair gene
polymorphisms and risk of pancreatic cancer. Clinical Cancer Research, 15: 740-746. PMID: 19147782. PMCID:
PMC26229144.
Thomas MB, Morris JS, Chadha R, Iwasaki M, Kaur H, Lin E, Kaseb A, Glover K, Davila M, and Abbruzzese J
(2009). Phase II trial of the combination of Bevacizumab and Erlotinib in patients who have advanced
hepatocellular carcinoma. Journal of Clinical Oncology, 27(6): 843-850.
Overman MJ, Varadhachary GR, Kopetz S, Adinin R, Lin E, Morris JS, Eng C, Abbruzzese JL, and Wolff RA
(2009). Phase II study of Capecitabine and Oxaliplatin for advanced adenocarcinoma of the small bowel and
ampulla of vater. Journal of Clinical Oncology, 2009 Jan 21 (Epub ahead of print).
Kamat P, Wen S, Morris JS, and Anandasabapathy S (2009). Exploring the association between elevated body
mass index and Barrett’s esophagus: a systematic review and meta-analysis. Annals of Thoracic Surgery, 87(2):
655-662.
Zuo X, Morris JS, Broaddus R, and Shureiqi I (2009). 15-LOX-1 transcription suppression through the NuRD
complex in colon cancer cells. Oncogene 28(12): 1496-1505.
Fleming JB, Gonzalez RJ, Petzel MQ, Lin E, Morris JS, Gomez H, Lee JE, Crane CH, Pisters PW, Evans DB
(2009). Influence of obesity on cancer-related outcomes after pancreatectomy to treat pancreatic adenocarcinoma.
Arch Surg. 144(3): 216-221.
Zuo X, Peng Z, Moussalli MJ, Morris JS, Broaddus RR, Fischer SM, and Shureiqi I (2009). Targeted PPAR-δ
genetic disruption profoundly inhibits colon tumorigenesis. Journal of the National Cancer Institute, 101(10):
762-767. PMID: 19436036. PMCID: PMC2684551.
Li D, Morris JS, Li J, Hassan MH, Day RS, Bondy ML, and Abbruzzese JL (2009). Body mass index and risk, age
of onset, and survival in pancreatic cancer patients. Journal of the American Medical Association, 301(24), 25532562. PMID: 19549972. PMCID: PMC2760963.
Morris JS (2009). Review of “Wavelet Methods in Statistics with R” by GP Nason. Biometrics, 65(2): 667-668.
Cradock AL, Melly SJ, Allen JG, Morris JS, Gortmaker SL (2009). Youth destinations associated with objective
measures of physical activity in adolescents. Journal of Adolescent Health, 45(3): S91-98. PMID: 19699443.
PMCID: PMC3260553.
183
[90]
[91]
[92]
[93]
[94]
[95]
[96]
[97]
[98]
[99]
[100]
[101]
[102]
[103]
[104]
[105]
[106]
[107]
[108]
Morris JS, Clark BN, Wei W, and Gutstein HB (2010): Evaluating the performance of new approaches to spot
quantification and differential expression in 2-dimensional gel electrophoresis studies. Journal of Proteome
Research, 9(1): 595-604. PMID: 19919108. PMCID: PMC2802214.
Morris JS (2010): Member’s Discoveries: Fatal flaws in cancer research. IMS Bulletin, 39(1), 5.
Dowsey AW, Morris JS, Gutstein HG, Yang GZ (2010): Informatics and Statistics for Analyzing 2-D Gel
Electrophoresis Images. Methods in Molecular Biology, 604: 239-255 PMID: 20013375. NIHMSID: 478641
Morris JS, Wu C, Coombes KR, Baggerly KA, Wang J, and Zhang L (2010). Alternative Probeset Definitions for
Combining Microarray Data Across Studies Using Different Versions of Affymetrix Oligonucleotide Arrays.
Meta-Analysis and Combining Information in Genetics and Genomics, eds. Rudy Guerra and Darlene Goldstein,
Chapman-Hall, 157-174.
Kopetz S, Hoff PM, Morris JS, Wolff RA, Eng C, Glover K, Adinin R, Overman M, Valero V, Wen S, Lieu C,
Yan S, Tran H, Ellis LM, Abbruzzesse JL, and Heymach JV (2010). Phase II Trial of Infusional 5-Fluorouracil,
Irinotecan and Bevacizumab (FOLFIRI+B) for Metastatic Colorectal Cancer: Efficacy and Circulating Angiogenic
Biomarkers Associated with Therapeutic Resistance. Journal of Clinical Oncology, 28(3):453-459. PMID:
20008624. PMCID: PMC2815707.
Malloy EJ, Morris JS, Adar SD, Suh HH, Gold DR, and Coull BA (2010): Wavelet-based functional linear mixed
models: an application to measurement error corrected distributed lag models. Biostatistics 11(3): 432-52, Epub
2010 Feb 15, PMID: 20156988. PMCID: PMC2883305.
Morris JS, Baggerly KA, Gutstein HB, and Coombes KR (2010). Statistical contributions to proteomic research.
Methods in Molecular Biology, 641:143-166. PMID: 20407946. NIHMS 261718.
Baladandayuthapani V, Ji Y, Talluri R, Nieto-Barajas LE, and Morris JS (2010). Bayesian Random Segmentation
Models to Identify Shared Copy Number Aberrations for Array CGH Data. Journal of the American Statistical
Association, 105(492): 1358-1375. PMID: 21512611. PMCID: PMC3079218
Katz R, He W, Khanna A, Fernandez R, Zaidi T, Krebs M, Caraway N, Zhang H, Jiang F, Spitz M, Blowers D,
Jimenez C, Mehran R, Swisher S, Roth J, Morris JS, Etzel C, and El-Zein R (2010). Genetically Abnormal
Circulating Cells in Lung Cancer Patients an Antigen Independent Fluorescence in-situ Hybridization-Based CaseControl Study. Clinical Cancer Research 16(15): 3976-87 Epub 2010 Jul22 (PMID: 20651054, PMCID:
PMC2949278).
Shureiqi I, Chen D, Day RS, Hochman FL, Ross W, Cole RA, Moy O, Morris JS, Xiao L, Newman R, Yang P,
and Lippman SM (2010). Profiling Lipoxygenase Metabolism in Specific Steps of Colonic Tumorigenesis. Cancer
Prevention Research 3(7): 829-38. (PMID: 20570882).
Kaseb A*, Xiao L, El-Deeb A, Kumar V, Lin E, Abdalla EK, Vauthey JN, Curley SA, Ellis L, Abbruzzese JL,
Hassan MM, and Morris JS* (2010). V-CLIP: Integrating plasma VEGF level into a new scoring system to stratify
patients with hepatocellular carcinoma. Cancer 2010 Dec 14.[Epub ahead of print] PMID:21157958. PMCID:
PMC3066286. (*Joint corresponding authors)
Dowsey AW, English JA, Lisacek F, Morris JS, Yang GZ, and Dunn MJ (2010). Image analysis tools and
emerging algorithms for expression proteomics. Proteomics, 10(23), 4226-4257. PMID: 21046614. PMCID:
PMC3257807.
Dowsey AW, English JA, Lisacek F, Morris JS, Yang GZ, and Dunn MJ (2011). Advance Article A22975: Image
Analysis Tools in Proteomics. Encyclopedia of Life Sciences. John Wiley & Sons, Ltd.
eScholarID:148685|DOI:10.1002/97804770015902.a0006216.pub2.
Morris JS, Baladandauthapani V, Herrick RC, Sanna PP, and Gutstein HG (2011). Automated analysis of
quantitative image data using isomorphic functional mixed models, with application to proteomic data. Annals of
Applied Statistics, 5(2A): 894-923. PMCID: PMC3298181.
Fogelman D, Jafari M, Varadhachary GR, Xiong H, Chang D, Bullock S, Ozer H, Bennett B, Cunningham P, Lin
E, Morris JS, Abbuzzesse JL, and Wolff RA (2011). Bevacizumab plus Gemcitabine and Oxaliplatin as First-Line
Therapy for Metastatic or Locally Advanced Pancreatic Cancer: A Phase II Study. Cancer Chemotherapy and
Pharmacology, 68(6): 1431-1438.
Zhu H, Brown PJ, and Morris JS (2011). Robust, Adaptive Functional Regression in Functional Mixed Model
Framework. Journal of the American Statistical Association, 106(495): 1167-1179. PMID: 22308015. PMCID:
PMC3270884.
Diao L, Clarke CH, Coombes KR, Hamilton SR, Roth J, Mao L, Czerniak B, Baggerly KA, Morris JS, Fung ET,
and Bast, Jr. RC (2011). Reproducibility of SELDI spectra across time and laboratories. Cancer Informatics, 2011
Mar 14: 10:45-64. PMCID: PMC3085423.
Kaseb A*, Abbruzzese JL, Vauthey JN, Aloia TA, Abdalla EK, Hassan MM, Lin E, Xiao L, El-Deeb AS, Rashid
A, and Morris JS* (2011). I-CLIP: Improved Stratification of Advanced Hepatocellular Carcinoma Patients by
Integrating Plasma IGF-1 into CLIP Score. Oncology, 80(5-6): 373-381. (* Joint corresponding authors). PMID:
21822028. PMCID: PMC3171278.
Moussalli MJ, Wu Y, Zhu X, Yang XL, Wistuba II, Raso MG, Morris JS, Bowser JL, Minna JD, Lotan R, and
Shureiqi I (2011): Mechanistic Contribution of Ubiquitous 15-Lipoxygenase-1 Expression Loss in Cancer Cells to
184
[109]
[110]
[111]
[112]
[113]
[114]
[115]
[116]
[117]
[118]
[119]
[120]
[121]
[122]
[123]
[124]
[125]
[126]
[127]
[128]
Terminal Cell Differentiation Evasion. Cancer Prevention Research, 2011 Aug 31. PMID: 21881028. PMCID:
PMC3232310.
Kaseb AO, Morris JS, Hassan MM, Siddiqui AM, Lin E, Xiao L, Abdalla EK, Vauthey JN, Aloia TA, Krishnan S,
and Abbruzzese JL (2011). Clinical and Prognostic Implications of IGF-1 and VEGF in Patients with
Hepatocellular Carcinoma. Journal of Clinical Oncology, 2011 Sep 12. PMID: 2191725. PMCID: PMC3189091.
Sabath N, Morris JS, and Graur D (2011): Is there a twelfth protein-coding gene in the genome of influenza A?
A selection-based approach to the detection of overlapping genes in closely related sequences. Journal of
Molecular Evolution, 73:305-315.
Hrafnkelsson B, Morris JS, Baladandayuthapani V (2012). Spatial Modeling of Annual Minimum and Maximum
Temperature in Iceland. Meteorology and Atmospheric Physics, 116(1-2): 43-61.
Morris JS (2012): Statistical Methods for Proteomic Biomarker Discovery using Feature Extraction or Functional
Data Analysis Approaches, Statistics and its Interface, 5(1), 117-136. NIHMS: 347640 (Awaiting PMC release).
Kaseb A, Garrett-Mayer E , Morris JS, Hassan MM, Hassabo H, Iwasaki M, Deaton L, Lin E, Xiao L, Onecescu
G, Abbruzzesse JL, and Thomas MB (2012). Final results, clinical and molecular predictors of outcome from
bevacizumab and erlotinib phase II trial in advanced hepatocellular carcinoma. Oncology, 82(2): 67-74.
Kaseb, AO, Morris JS, Hassan MM, and Abbruzzese JL (2012): Reply to A. Goyal et al. Journal of Clinical
Oncology, 30(9): 1019-1020.
Morris JS (2012): Review of “Functional Data Analysis with R and MATLAB” by J. Ramsay, G. Hooker, and S.
Graves. The American Statistician, 65(4):6-7.
Zhu H, Brown PJ, and Morris JS (2012): Robust classification of functional and quantitative image data using
functional mixed models. Biometrics, 68(4): 1260-1268. DOI: 10.1111/j.1541-0420.2012.01765.x PMID:
22670567. PMCID: PMC3443537.
Jennings EM, Morris JS, Carroll RJ, Manyam GC, and Baladandayuthapani V (2012). Hierarchical Bayesian
methods for integration of various types of genomic data. Proceedings, Genomics Signal Processing and Statistics
(GENSIPS), December 2, 2012. (refereed proceedings)
Zuo X, Peng Z, Wu Y, Moussalli MJ, Yang XL, Wang Y, Parker-Thornburg J, Morris JS, Broaddus RR, Fischer
SM, and Shureiqi I (2012). Effects of gut-targeted 15-LOX-1 transgenic expression on colonic tumorigenesis in
mice. Journal of the National Cancer Institute, 104(9): 709-716. PMID: 22472308. PMCID: PMC3341308.
Wang W, Baladandayuthapani V, Morris JS, Broom BM, Manyam GC, and Do KA (2013). iBAG: Integrative
Bayesian Analysis of High-Dimensional Multi-platform Genomic Data. Bioinformatics, 29(2): 149-159. DOI:
10.1093/bioinformatics/bts655. PMID: 23142963. PMCID: PMC3546799.
Crainiceanu CM, Caffo BS, and Morris JS (2013): Multilevel Functional Data Analysis. SAGE Handbook for
Multilevel Modeling, Simonoff and Marx, eds., Chapter 13, pages 223-248.
Lynch P*, Morris JS*, Ross W, Rodriguez-Bigas M, Posadas J, Weber D, Sepeda V, Levin B, and Shureiqi I (2013)
Global quantitative assessment of the colorectal polyp burden in familial adenomatous polyposis by using a webbased tool. Gastrointestinal Endoscopy, 77(3): 455-463. PMID: 23332604. PMCID: PMC3574220 (* joint first
authors)
Martinez JG, Bohn KM, Carroll RJ and Morris JS (2013). A study of Mexican free-tailed bat syllables: Bayesian
functional mixed models for nonstationary acoustic time series. Journal of the American Statistical Association,
108(502): 514-526. PMID: 23997376 PMCID: PMC3755785.
Fazio MA, Grytz R, Morris JS, Bruno L, Gardiner S, Girkin CA, and Downs JC (2013). Age-related changes in
human peripapillary scleral stiffness. Biomechanics and Modeling in Mechanobiology, 2013 Jul30. PMID:
23896936 PMCID: PMC3875631.
Raghav KPS, Shetty AV, Kazmi SMA, Zhang N, Morris JS, Taggert M, Fournier K, Royal R, Mansfield P, Eng C,
Wolff RA, and Overman MJ (2013). Impact of Molecular Alterations and Targeted Therapy in Appendiceal
Adenocarcinomas. The Oncologist, 18(12): 1270-1277 PMID: 24149137 PMCID: PMC3868421.
Jennings EM, Morris JS, Carroll RJ, Manyam GC and Baladandayuthapani V (2013). Bayesian methods for
expression-based integration of various types of genomics data. EURASIP Journal on Bioinformatics and
Systems Biology, 13, doi:10.1186/1687-4153-2013-13.
Lieu C, Tran H, Jian Z, Mao M, Overman M, Chen Z, Eng C, Morris JS, Ellis L, Heymach J, and Kopetz S
(2013). The association of alternate VEGF ligands with resistance to anti-VEGF therapy in metastatic colorectal
cancer (mCRC), PLOS ONE, 8(10), 2013 Oct 15; e77117. PMID: 24143206 PMCID: PMC3797099.
Liao L, Moschidis E, Riba-Garcia I, Unwin R, Dunn W, Morris JS, Graham J and Dowsey A (2013). A workflow
for novel image-based differential analysis of LC-MS experiments. Proceedings of 61st ASMS Conference on
Mass Spectrometry and Allied Topics. Minneapolis, Minnesota, 9th – 13th Jun. eScholarID:209955. (refereed
proceedings).
Olivares RJ, Rao A, Rao G, Morris JS, and Baladandayuthapani V (2013). Integrative analysis of multi-modal
correlated imaging-genomics data in glioblastoma. Proceedings, Genomics Signal Processing and Statistics
(GENSIPS), November 17-19, 2013. (refereed proceedings)
185
[129]
[130]
[131]
[132]
[133]
[134]
[135]
[136]
[137]
[138]
[139]
[140]
[141]
[142]
[143]
[144]
[145]
[146]
[147]
Eberth JM, Eschbach K, Morris JS, Nguyen H, Hossain M, and Elting L (2014). Geographic disparities in
mammography capacity in the South: a longitudinal assessment of supply and demand. Health Services Research,
49(1): 171-185. PMID: 23829179.
Kaseb AO, Shah N, Hassabo H, Morris JS, Xiao L, Abaza Y, Soliman K, Lee J, Vauthey J, Wallace M, Aloia T,
Curley S, Abbruzzese J, and Hassan M (2014). Reassessing hepatocellular carcinoma staging in a changing patient
population. Oncology, 86(2): 63-71. PMID: 24401634.
Davidian M, Lin X, Morris JS, and Stefanski LA, eds. (2014). The Work of Raymond R. Carroll – The Impact
and Influence of a Statistician. Springer.
Kaseb AO, Xiao L, Hassan MM, Chae YK, Lee JS, Vauthey JN, Krishnan S, Cheung S, Hassabo HM, Aloia T,
Conrad C, Curley SA, Vierling JM, Jalal P, Raghav K, Wallace M, Rashid A, Abbruzzese JL, Wolff RA, and Morris
JS (2014). Development and validation of an IGF-1 score to assess hepatic reserve in hepatocellular carcinoma.
Journal of the National Cancer Institute, 106(5).
Zuo X, Xu M, Yu J, Wu Y, Moussalli MJ, Manyam GC, Lee SI, Liang S, Morris JS, Broaddus R, Shureiqi I (2014).
Potentiation of colon cancer susceptibility in mice by colonic epithelial PPAR-overexpression. Journal of the
National Cancer Institute, 106(4).
Zhang L, Morris JS, Zhang J, Orlowski RZ, and Baladandayuthapani V (2014). Bayesian joint selection of genes
and pathways: Applications in multiple myeloma genomics. Cancer Informatics, 13(S2), 113-123.
Liao H, Moschidis E, Riba-Garcia I, Zhang I, Unwin R, Morris JS, Graham J and Dowsey A (2014). A new
paradigm for clinical biomarker discovery and screening with mass spectrometry based on biomedical image
analysis principles. IEEE International Symposium on Biomedical Imaging. Beijing, China. eScholarID:219592
(refereed proceedings).
Jeter CB, Patel S, Morris JS, Butler I, and Sereno A (2015). Oculomotor Executive Function Abnormalities with
Increased Tic Severity in Tourette Syndrome, The Journal of Child Psychology and Psychiatry, to appear.
Kee BK, Morris JS, Slack RS, Crocenzi T, Wong L, Esparaz B, Overman M, Glover K, Jones D, Wen S, and Fisch
MJ (2015). A phase II, randomized double-blind trial of calcium aluminosilcate clay versus placebo for the
prevention of diarrhea in patients with metastatic colorectal cancer treated with irinotecan. Supportive Care in
Cancer, to appear.
Morris JS. (2015). Functional regression. Annual Review of Statistics and its Application, 2, to appear.
Morris JS, Gutstein HG (2015). Detection and Quantification of Protein Spots by Pinnacle: Methods in Molecular
Biology: 2D Gel Data Analysis, to appear.
Jennings EM, Morris JS, Manyam GC, Carroll RJ, and Baladandayuthapani V (2015). Bayesian models for flexible
integrative analysis of multi-platform genomic data. Integrating Omics Data: Statistical and Computational
Methods, George C. Tseng, Xianghong Jasmine Zhou, Debashis Ghosh, eds., to appear.
Fazio M, Grytz R, Morris JS, Bruno L, Girkin C, and Downs JC (2015). Scleral structural stiffness increases more
rapidly with age in donors of African descent compared to donors of European descent. Investigative
Ophthalmology & Visual Science, to appear.
Lynch P, Burke C, Phillips R, Morris JS, Wang X, Liu J, Slack R, Patterson S, Sinicrope F, Rodriguez-Bigas M,
Half E, Bulow S, Latchford A, Hasson H, Richmond E, and Hawk E. (2015). An international randomized trial
of celecoxib versus celecoxib plus difuoromethylomithine in patients with familial adenomatous polyposis. Gut, to
appear.
Tchumtchoua S, Dunson D, and Morris JS (2015). Online variational Bayes inference for high-dimensional
correlated data. JCGS, to appear.
Calin G, Tudor S, Giza D, Lin HY, Yoshiaki K, D’Abundo L, Toale K, Shimizu M, Ferracin M, Challagundla K,
Cortez M, Fuentes-Mattei E, Tullbure D, Gonzalez C, Henderson J, Row M, Rice T, Ivan C, Negrini M, Fabbri
M, Morris JS, Yeung SC, Vasilescu C, and Fabris L (2015). Cellular and Kaposi’s sarcoma-associated herpes virus
microRNAs in sepsis and surgical trauma. Cell Death and Disease, to appear.
Lancia L, Rausch P, and Morris JS (2015). Automatic quantitative analysis of ultrasound tongue contours via
wavelet-based functional mixed models. Journal of Acoustical Society of America, to appear.
Meyer MJ, Coull BA, Versace F, Cinciripini P, and Morris JS (2015). Bayesian function-on-function regression for
multi-level functional data. Biometrics, to appear.
Chen ZY, Raghav K, Lieu C, Jiang ZQ, Eng C, Vauthey JN, Chang GJ, Qiao W, Morris JS, Hong D, Hoff P,
Tran H, Heymach J, Overman M, and Kopetz S(2015). Cytokine profile and prognostic significance of high
neutrophil-lymphocyte ratio in metastatic colorectal cancer. British Journal of Cancer, to appear.
Submitted Papers:
[1]
Morelli MP, Overman MJ, Dasari A, Kazmi SMA, Vilar E, Morris VK, Lee MS, Harron D, Eng C, Morris JS, Kee
BK, Deaton FL, Garrett C, Diehl F, Angenendt P and Kopetz S: Heterogeneity of acquired KRAS and EGFR
mutations in colorectal cancer patients treated with anti-EGFR monoclonal antibodies.
[2]
Figueiredo JC, Mott LA, Hamilton SR, Morris JS, Ahnen D, Barry E, …, and Baron JA: Protein expression
patterns in colorectal adenomatous polyps and serrated lesions using tissue microarray analysis.
186
[3]
[4]
[5]
[6]
[7]
[8]
[9]
Baladandayuthapani V, Abruzzo LV, Coombes KRC, and Morris JS: Bayesian adaptive spline-based functional
regression with application to copy number data.
Zhang L, Baladandayuthapani V, Baggerly K, Czerniak B, and Morris JS. Functional CAR models for spatially
correlated high-dimensional functional data. Under revision for JASA-TM.
Chen J, Chen JS, Zhang J, Phan L, Munoz NM, Katz LH, Farci P, Su X, Pandita TK, Zamboni F, Shetty K, Wu
X, Rashid A, Mishra B, Shaw KR, Herlong F, Morris JS, and Mishra L: Genomic landscape of human liver cancer
reveals TGF-B signaling signatures with prognostic significance. Submitted.
Hassan MM, Abdel-Wahab R, Kaseb A, Phan AT, El-Serag HB, Morris JS, Raghav KPS, Lee JS, Vauthey JN,
Shalaby A, Torres H, Amos CI, and Li D. Significance of early adulthood obesity on risk and prognosis of
hepatocellular carcinoma in the United States. Submitted.
Lee W and Morris JS. Identification of differentially methylated loci using wavelet-based functional mixed models.
Submitted.
Guinney J, Dienstmann R, Wang X, de Reynies A, Schlicker A, Soneson C, Marisa L, Roepman P, Nyamundanda
G, Angelino P, Bot BM, Morris JS, Simon I, Gerster S, Fessler E, de Sousa e Melo F, Missiaglia E, Ramay H,
Barras D, Homicsko K, Maru D, Manyam GC, Broom B, Boige V, Laderas T, Salazar R, Gray JW, Tabernero J,
Bernards R, Friend SH, Laurent-Puig P, Medema JP, Sadanandam A, Wessels L, Delorenzi M, Kopetz S,
Vermeulen L, and Tejpar S. The consensus molecular subtypes of colorectal cancer. Submitted to Nature
Genetics.
Kaseb AO, Xiao L, Hassan MM, Chae YK, Lee JS, Vauthey JN, Krishnan S, Cheung S, Hassabo HM, Aloia T,
Conrad C, Curley SA, Vierling JM, Jalal P, Raghav K, Wallace M, Rashid A, Abbruzzese JL, Wolff RA, and Morris
JS (2014). Reply to Shao et al. RE: Development and validation of an IGF-1 score to assess hepatic reserve in
hepatocellular carcinoma. Submitted.
INSTRUCTION AND MENTORING
Formal Teaching Experience:
[1] High school teacher, Northside Christian School (1993-1995): taught high school mathematics and physics,
coached basketball and golf, before returning to graduate school in Statistics.
[2] Teaching Assistant, Texas A&M University (Fall 1995): served as grader for graduate level Statistics course.
[3] Teaching Assistant/Instructor, Texas A&M University (Spring 1996, Summer 1996 x 2, Fall 1996, Spring 1997,
Fall 1997): served as sole instructor for introductory undergraduate statistics courses (STAT301/STAT302) for
non-mathematical majors, giving all lectures, preparing all homeworks and exams, and holding full office hours.
[4] Assistant Lecturer, Texas A&M University (Spring 1998): served as sole instructor for undergraduate Statistics
courses for engineering majors (STAT211), giving all lectures, preparing homeworks and exams, and holding full
office hours.
Postdoctoral Researchers:
[1] Andrew Dowsey (EPSRC Postdoctoral Fellowship), 2008-2010. (Reader, University of Liverpool)
[2] Hongxiao Zhu, 2009-2011. (Assistant Professor, Virginia Tech University)
[3] Lin Zhang (co-advise with Veera Baladandayuthapani), 2012-.
[4] Wonyul Lee, 2013-.
[5] Bruce Bugbee (co-advise with Veera Baladandayuthapani), 2014Students:
[1] Jijun Xu, PhD, GSBS, Advisory Committee, 2004-2006.
[2] Katherine Barker, PhD, GSBS, Advisory Committee, 2004-2009.
[3] Michael Lecocke, PhD, Rice, Advisory Committee, 2003-2005.
[4] Alena Ixmoscane Scott, PhD, Rice, Advisory Committee, 2004-2006.
[5] Julie Beaver, MS, UT School of Public Health, Predoctoral Fellow, 2004.
[6] Cameron Jeter, PhD, GSBS, Advisory Committee, 2008-2010.
[7] Jens Johansson, PhD, University of Copenhagen, Mentor, 2009.
[8] Changlu Liu, PhD, GSBS, Tutorial Mentor, 2009.
[9] Pan Tong, PhD, GSBS, Supervisory Committee, 2009-2010.
[10] Selina Vattithil, PhD, GSBS, Advisory Committee, 2010-2014.
[11] Chunyan Cai, PhD, GSBS, Chair, Examination Committee, 2010.
[12] Haiying Pang, PhD, GSBS, Examination Committee, 2010.
[13] Casey Schultz, PhD, GSBS, Advisory Committee, 2010-2011.
[14] Justin Wong, PhD, GSBS, Advisory Committee, 2012-present, Examination Committee, 2013
[15] Isaac Wun, PhD, GSBS, Advisory Committee, 2012-2014.
[16] Samuel Fahrenholtz, PhD, GSBS, Examination Committee, 2012.
[17] Elizabeth Jennings, PhD, Texas A&M, co-advisor (Ray Carroll, Veera B. 2012-present).
[18] TJ Dai, PhD, GSBS, Tutorial Mentor, 2013.
187
[19] Chen Jiong, PhD, GSBS, Tutorial Mentor, 2013, Advisory Committee 2013-present, Examination Committee
2014.
[20] Jialu Li, PhD, GSBS, Advisory Committee, 2013-present.
[21] Zeya Wang, Rice University, co-advisor (Wenyi Wang), 2013-present.
[22] Alexander Davis, PhD, GSBS, Tutorial Mentor, 2014; Advisory Committee 2014-present.
Invited Presentations and Seminars:
I have presented 135 invited lectures, including the following:
Mayo Clinic
Iowa State University
University of Michigan
University of Florida
University of New Mexico
University of Chicago
Duke University
Fred Hutchinson Cancer Research Center
North Carolina State University
The University of Texas MD Anderson Cancer Center
Rice University
University College of London
University of Kent, Canterbury UK
Southern Methodist University
Mississippi State University
Texas A&M University
Yale University
Harvard University
University of North Carolina
Texas A&M University
St. Cloud State University
ENAR Spring Meeting
7th Valencia International Meeting on Bayesian Statistics
ENAR Spring Meeting
WNAR Summer Meeting
Joint Statistical Meetings
Critical Assessment of Microarray Data Analysis
Texas A&M University
University of Texas, School of Public Health
ENAR Spring Meeting
ISBA World Meetings
International Biometrics Conference
Advancing Practice, Instruction, and Innovation through Informatics
Rice University
Texas A&M University
Los Alamos National Laboratories
University of Pennsylvania
Harvard University
ENAR Spring Meeting
EMR Meeting of the IBS
ICSA Applied Statistics Symposium
WNAR Summer Meeting
Joint Statistical Meetings
Johns Hopkins University
University of Texas, Dallas
ICSA Applied Statistics Symposium
International Workshop on Applied Probability
Clinical Proteomics in Oncology Conference
Joint Statistical Meetings
University of Washington
University of Minnesota
International Indian Statistical Association Meeting
ENAR Spring Meeting
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2001
2001
2001
2001
2001
2001
2002
2002
2002
2002
2002
2002
2002
2003
2003
2003
2003
2003
2003
2004
2004
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
2006
2007
2007
188
Current and Future Trends in Nonparametrics
Institute for Pure and Applied Mathematics Workshop
McGill University
Columbia University
Brown University
National Institute of Allergy and Infections Diseases
University of North Carolina
North Carolina State University
Georgetown University
University of Michigan
St. Mary’s University
Wyeth, Functional Mixed Models Short Course
ENAR Spring Meeting
Statistical Theory and Methods for Complex, High-Dimensional Data
SRCOS Summer research Conference
WNAR Summer Meeting
International Biometrics Conference
ISBA World Meetings
Prairie View A&M University
Imperial College London
Fred Hutchinson Cancer Research Center
Texas A&M University
Rice University
University of Rochester
WNAR Summer Meeting
Joint Statistical Meetings
International Statistical Institute Meetings
University of South Carolina
Kansas University Medical Center
ENAR Spring Meeting
University of Buffalo (Distinguished Scholars Lecture Series)
SRCOS Meetings
Hong Kong University
Joint Biostatistics Symposium, China
Joint Statistical Meetings
North Carolina State University
Duke University
SAMSI Workshop on Longitudinal and Functional Data
Messiah College
Thomas Jefferson University
University of Pennsylvania
Emory University
University of Georgia
University of Missouri
ENAR Spring Meeting
High Dimensional Statistics: Advances and Challenges, Singapore
Statistical Methods for Very Large Data Sets Conference, JHSPH
SAMSI Analysis of Object Data Program Transition Workshop
University of North Carolina
Joint Statistical Meetings
Myrto Lefkopoulou Distinguished Lecture, Harvard University
Case Studies in Bayesian Statistics & Machine Learning, Carnegie-Mellon
Texas A&M University
North Carolina State University
University of North Carolina
Workshop on Bioinformatics, Biostatistics, & Biology of Nutrition/Cancer
Interface 2012, Rice University
ISBA World Meetings, Kyoto, Japan
IMS-APRM 2012, Tsukuba, Japan
Joint Statistical Meetings
BASS Meetings, Savannah, GA
2007
2007
2007
2007
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2010
2010
2010
2010
2010
2010
2010
2010
2010
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2012
2012
2012
2012
2012
2012
2012
2012
189
MD Anderson Biostatistics Grand Rounds
Young Investigator Workshop, ENAR Spring Meeting
Conference of Texas Statisticians (COTs), Houston, TX
Virginia Tech University, Blacksburg, VA
High Dimensional Inference with Applications, Canterbury, UK
Oxford University, Oxford, UK
University of Manchester Biostatistics, Manchester, UK
University of Manchester CADET, Manchester, UK
University of Nottingham, Nottingham, UK
European Meeting of Statisticians, Budapest, Hungary
Joint Statistical Meetings, Montreal, Quebec
University of Washington Statistics/Biostatistics, Seattle, WA
Bayesian Biostatistics 7 Meeting, Houston, TX
ENAR Spring Meeting, Baltimore, MD
International Biometrics Conference, Florence, IT (selected contributed)
ISBA World Meetings, Cancun, Mexico
Joint Statistical Meetings, Boston, MA
BASP Frontiers Workshop, Switzerland
Duke University, Durham, NC
University of Alabama, Birmingham, AL
Michigan Imaging Workshop, Ann Arbor, MI
BIRS Workshop on Frontiers in Functional Data Analysis, Banff
Joint Statistical Meetings, Seattle WA
2012
2013
2013
2013
2013
2013
2013
2013
2013
2013
2013
2013
2014
2014
2014
2014
2014
2015
2015
2015
2015
2015
2015
PROFESSIONAL SERVICE
Editorial Responsibilities:
• Associate Editor, Biometrics (2006-2011) (handled 50 submissions).
• Associate Editor, Journal of the Royal Statistical Society, Series B, (2006-2011) (47 papers).
• Associate Editor, Annals of Applied Statistics (IMS), (2006-2015) (handled 74 submissions).
Journal Reviewer:
I have reviewed over 100 journal articles, including articles in:
Journal of the American Statistical Association, Journal of the Royal Statistical Society (Series B), Biometrics, Annals of Statistics,
Annals of Applied Statistics, Statistical Science, Biostatistics, Technometrics, Journal of Computational and Graphical Statistics,
Journal of the Royal Statistical Society (Series C), Journal of Statistical Planning and Inference, Statistics in Medicine, Journal of
Agricultural, Biological, and Environmental Statistics, International Journal of Statistics, Bioinformatics, PLoS One, Proteomics,
Proteins, BMC Bioinformatics, Current Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics,
IEEE Transactions on Medical Imaging, Genomic Signal Processing, Science Translational Medicine, New England Journal of
Medicine, Journal of the National Cancer Institute, Cancer Informatics, Communications in Statistics, Journal of VLSI Signal
Processing, Clinical Cancer Research, Neuropharmacology, Nucleic Acids Research, Molecular and Cellular Proteomics, Journal of
Cellular and Molecular Medicine, Chemometrics and Intelligent Laboratory Systems, Journal of Microscopy, Physiological Genomics,
Drug Information Journal, International Journal of Imaging Systems and Technology, International Journal of Molecular Science.
Conference Organizer:
• Invited Session Organizer, ENAR 2002.
• Invited Session Organizer, WNAR 2003.
• Session Organizer, Conference of Texas Statisticians, 2003.
• Invited Session Organizer, ENAR 2005.
• Invited Session Organizer, WNAR 2005.
• Topic Contributed Session Organizer, IBC 2006.
• Program Chair, Biometrics Section of the American Statistical Association, ENAR 2006.
• Invited Session Organizer, ENAR 2006.
• Invited Session Organizer, JSM 2006.
• Program Committee Member, ENAR 2007.
• Invited Session Organizer, ENAR 2007.
• Member, Organizing Committee, “Statistical Methods for Complex Data” 2009.
• Invited Session Organizer, JSM 2009.
• Program Co-chair, ENAR 2010.
• IMS Invited Session Organizer, ENAR 2010.
190
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Organizing Committee, “Bayesian Biostatistics” 2010.
Organizing Committee, SRCOS 2010.
Invited Session Organizer, SRCOS 2010.
Organizing Committee, “Bayesian Biostatistics” 2011.
Special Late Breaking Session Organizing Committee, ENAR 2011.
Topic Contributed Session Organizer, JSM 2012.
Organizing Committee: “Bayesian Biostatistics” 2012.
Organizing Committee: “Interface Conference”, Rice University, 2012.
Topic Contributed Session Organizer, JSM 2013.
Organizing Committee: “Bayesian Biostatistics” 2014.
Invited Session Organizer, IBC 2014.
Invited Session Organizer, Michigan Imaging Workshop 2015.
Organizing Committee “iBRIGHT Integrative Genomics and Personalized Medicine” 2015
Program Chair, JSM 2016.
Other Professional Service:
• ENAR Regional Committee, 2013-2015.
• Member, Myrto Lefkopoulou Distinguished Lectureship Committee, 2012.
• Secretary, ENAR, 2011-2012.
• Council of Sections Representative, ASA Section on Nonparametric Statistics, 2010-2012.
• Member, DSMB, Aggenix, 2011-2012.
• H.O. Hartley Award Committee, Texas A&M University, 2010-.
• Member, OSMB for NHLBI grant, 2005-2008.
• NIH Study Section Member, R13 2009-2012, SBIR 2010, 2012.
• Susan G. Komen for the Cure’s Targeted Therapies-5 Study Section, 2009.
• Texas A&M Department of Statistics Alumni Board 2008-2013.
• Student Paper Review Committee, ENAR 2005-2007, 2013.
• Member of Regional Advisory Board, ENAR, 2004-2006.
• Student Paper Review Committee, WNAR 2004.
Institutional Service (MD Anderson):
• Institutional Tenure and Promotions Review Committee, 2014-present.
• Deputy Chair, Department of Biostatistics, 2011-present.
• Mentoring Coordinator, Department of Biostatistics, 2013-present.
• Co-Director, Joint MDACC-Rice Biostatistics Program, 2011-present.
• Director, Joint MDACC-TAMU Medical Statistics Program, 2011-present.
• Graduate Education Committee, GSBS, 2012-2015.
• Chair, Faculty Search Committee, 2012, 2015.
• Member, Faculty Search Committee, Behavioral Science Statistics 2012.
• Member, Faculty Search Committee, Bioinformatics 2014.
• Member, Faculty Search Committee, Biostatistics 2011.
• Faculty Achievement Awards Selection Committee, 2012.
• Clinical Research Council, MD Anderson Cancer Center, 2009-2012.
• Clinical Research Advisory Committee, 2011-present.
• Internal Advisory Board, Multiple Myeloma P01, 2006-2012.
• Internal Advisory Board, GU P01, 2009-2011.
• Study Section Member, Internal Research Grants, 2005-2008.
• Study Section Member, ACS Institutional Research Grants, 2008-2010.
• Member, Faculty Compensation Committee, MD Anderson Cancer Center, 2006-2009.
• Chair, Faculty Compensation Committee, MD Anderson Cancer Center, 2007-2009.
• Faculty Senator, MD Anderson Cancer Center, 2006-2011.
• Faculty Appeals Committee Member, MD Anderson Cancer Center, 2009-2012.
• Mid-tenure Review Committees, Veera Baladandayuthapani (Chair, 2009), Paul Scheet (Chair, 2012), Michele
Guindani (Chair, 2012), Wenyi Wang (Member, 2012), Han Liang (Member, 2013), Francesco Stingo (Chair,
2014)
191
SCOTT D. GRIMSHAW
Department of Statistics, Brigham Young University
219 TMCB, Provo, Utah 84602-6575
Voice: 801-422-6251 Email: [email protected]
EDUCATION:
1989 Ph.D., Statistics, Texas A&M University, College Station, TX
Dissertation: A Unified Approach to Estimating Tail Behavior. Chairman: Emanuel Parzen
1985
M.S., Statistics, Texas A&M University, College Station, TX
Thesis: Estimation of the Linear-Plateau Segmented Regression Model in the Presence of Measurement Error.
Chairman: P. Fred Dahm
1983
B.S., Mathematics, Southern Utah State College, Cedar City, UT
Magna Cum Laude
EXPERIENCE:
2004–
Professor, Department of Statistics, Brigham Young University, Provo, UT.
2010–
Statistician, BYU Broadcasting, Provo, UT.
1999-2004
Associate Professor, Department of Statistics, Brigham Young University, Provo, UT.
2001
Faculty Advisor, Washington Seminar, Brigham Young University, Provo, UT.
1999-2000
Visiting Research Analyst, Structured Transactions and Analytical Research, First Union Capital Markets,
Charlotte, NC.
1993-99
Assistant Professor, Department of Statistics, Brigham Young University, Provo, UT.
1989-93
Assistant Professor (tenure track), Management Science and Statistics, College of Business and
Management, University of Maryland, College Park, MD.
1987-89
Research Assistant, Department of Statistics, Texas A&M University, College Station, TX.
1985-86
Statistics Internship Program, Jointly Sponsored by the Applied Statistics Group, Engineering
Department, E.I. du Pont de Nemours & Co. (Inc.), Wilmington, DE and the Department of
Statistics, Texas A&M University, College Station, TX.
HONORS & AWARDS:
• 2007 BYU Statistics Faculty Fellowship.
• 2005 H.O. Hartley Award, for Distinguished Service to the Discipline of Statistics by a Former Student of the
Texas A&M Statistics Department.
• 2005 BYU Statistics Chair’s Outstanding Paper Award.
• 2005 BYU Statistics Teacher of the Year.
• 2003 BYU Statistics Chair’s Outstanding Paper Award.
• 2001 Frank Wilcoxon Prize for the Best Practical Application Paper in Technometrics.
• 1997 Best Contributed Paper in Statistics, Data Analysis, and Modeling Section, Twenty- Second Annual SAS
Users Group International Conference.
• 1987 W.S. Connor Memorial Award, Outstanding Ph.D. candidate, Department of Statis- tics, Texas A&M
University.
SERVICE TO SPONSORING INSTITUTION
• 2014–2015 Faculty Advisory Council, College of Physical and Mathematical Sciences Representative.
• 2014–15, Teaching Committee
• 2013 Mathematical Sciences Committee Evaluating ENGL 316, College of Physical and Mathematical Sciences.
• 2012 Modeling Donor Affinity to BYU Colleges and Units, LDS Philanthropy.
• 2012 Impact of PBS Host Event on Preschool Reading, KBYU Eleven.
• 2010–12 Teaching and Learning Committee Chair, Department of Statistics.
• 2008–12 Rank and Status Committee, Department of Statistics.
• 2006–10 Associate Chair, Department of Statistics.
Responsible forfaculty teaching assignments, program learning outcomes and assessment that led to a new
curriculum that satisfies ASA Undergraduate Statistics Guidelines.
• 2006–10 Graduate Coordinator, Department of Statistics.
Changed the graduate culture from one were 60% of students took longer than the stated 2 years to graduate.
Since Fall 2006 all admitted students complete degree in 2 years or less. Worked with students who had left the
192
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
program to complete project or thesis and graduate (last two graduated April 2008). Grew the BS/MS Statistics
Integrated program as the department’s flagship undergraduate experience.
2008–10 Resources Subcommittee of Department Teaching and Learning Committee, Department of Statistics.
2008 Spring Research Conference Organizing Committee, College of Physical and Mathematical Sciences.
2007 Rank and Status Committee, College of Physical and Mathematical Sciences.
2005–07 University Academic Unit Review Committee.
2006 Summer Institute of Applied Statistics Organizer, R. Todd Ogden, “Essential Wavelets for Statistical
Applications and Data Analysis.”
2005 Search Committee Chair, Department of Statistics.
2002–03 Search Committee, Department of Statistics.
2002–04 Five-year Plan Committee, Department of Statistics.
2001–03 Scholarship and Awards Committee Chair, Department of Statistics.
2001 Faculty Advisor, Washington Seminar.
Supervised 31 BYU students that arrived in Washington, DC two weeks before the September 11 terrorist attack
on the Pentagon. Those events changed the student needs, many internship assignments, and some of the
Washington Seminar program. One highlight was a debriefing by the Honorable Robert Bennett, Senator (R-UT),
the day Congress recessed after the October anthrax letters were delivered to the Senate majority leader’s office.
2000 Co-Advisor of 2000 Utah Colleges Exit Poll, Departments of Statistics and Political Science.
One of four faculty advisors who mentored undergraduate statistics and political science students to perform the
ambitious sampling class project of a Utah statewide exit poll. The students are organized into a virtual polling
firm and committed over 2,500 man-hours to sample polling places throughout the state by training over 500
student pollsters from BYU and other Utah colleges and universities.
1999 Summer Institute of Applied Statistics Organizer, Raymond J. Carroll and David Ruppert, “Measurement
Error Models.”
1999 MS Comprehensive Exam Committee, Department of Statistics
1998–99 Curriculum Committee, Department of Statistics
1998 Summer Institute of Applied Statistics Organizer, Bradley P. Carlin, “Bayes and Empirical Bayes for Data
Analysis.”
1995 Electronic Classroom Evaluation and Review Task Force Chair, Assistant Aca- demic Vice-President,
Computing.
1995 Analysis of Time to Graduation at BYU (Alumni 1980–1994), Assistant Aca- demic Vice-President,
Computing.
1993– Business Emphasis Advisor, Department of Statistics.
SERVICE TO THE PROFESSION
• 2013–14 ASA Presidential Initiative: Committee to Revise the Curriculum Guidelines for Undergraduate Majors
and Minors in Statistics, Chair: Nicholas J. Horton, Amherst College.
• 2013–14 Past-President, Utah Chapter of the American Statistical Association.
• 2012–14 Associate Editor, Reviews in Journal of the American Statistical Association, and The American
Statistician.
• 2008– Texas A&M Statistics Alumni Advisory Board
• 1990– Referee, JASA, Technometrics, JQT, TAS, JCGS, Communications in Statis- tics, JSPI, JQAS
• 2012–13 President, Utah Chapter of the American Statistical Association.
• 2006–12 Associate Editor, Computational Statistics
• 2011–12 First Vice President, Utah Chapter of the American Statistical Association.
• 2011 SPES Fall Technical Conference Program Committee Chair
• 2010 SPES Fall Technical Conference Program Committee Representative
• 2007–09 H.O. Hartley Award Selection Committee, Texas A&M Statistics Department.
• 2007 Local Area Committee Chair, Joint Statistics Meeting, Salt Lake City, UT.
• 2005 Contributed Program Chair, Spring Research Conference on Statistics in In- dustry, Park City, UT.
• 2003 Invited Session Organizer, “Financial Risk and Fraud Detection,” Interface 2003, Salt Lake City, UT.
• 1998 Invited Session Organizer, “Utilizing Large Industrial Data Sets for Product and Process Quality
Improvement,” Joint Statistics Meetings, Dallas, TX.
• 1997 Special Contributed Paper Session Organizer, “Batch Process Monitoring Us- ing SPC,” Joint Statistics
Meetings, Anaheim, CA.
• 1996 Invited Session Organizer, “Tree-based Models,” Joint Statistics Meeting, Chicago, IL.
• 1995–97 Treasurer, Utah Chapter of the American Statistical Association.
• 1994–95 Second Vice President, Utah Chapter of the American Statistical Association.
193
•
1987–89 Treasurer, Southeast Texas Chapter of the American Statistical Association.
PUBLICATIONS:
Refereed:
1. Grimshaw, Scott D., and Burwell, Scott J. (2014). “Choosing the Most Popular NFL Games in a Local TV
Market.” Journal of the Quantitative Analysis of Sport, 10, 329–343.
2. American Statistical Association Undergraduate Guidelines Workgroup (2014). “2014 Cur- riculum Guidelines for
Undergraduate Programs in Statistical Science.” Alexandria, VA: American Statistical Association.
http://www.amstat.org/education/curriculumguidelines.cfm Members: Beth Chance, Steve Cohen, Scott
Grimshaw, Johanna Hardin, Tim Hester- berg, Roger Hoerl, Nicholas Horton (chair), Chris Malone, Rebecca
Nichols, Deborah Nolan.
3. Grimshaw, Scott D., Sabin, R. Paul, and Willes, Keith M. (2013). “Analysis of the NCAA Men’s Final Four TV
audience.” Journal of the Quantitative Analysis of Sport, 9,115–126.
4. Grimshaw, Scott D., Blades, Natalie J., and Miles, Michael P. (2013). “Spatial Control Charts for the Mean.”
Journal of Quality Technology, 45, 130–148.
5. Wilde, Sarah L., and Grimshaw, Scott D. (2013). “Efficient Computation of Generalized Median Estimators.”
Computational Statistics, 28, 307–317.
6. Dahlin, Eric C., Strong, A. Brent, and Grimshaw, Scott D. (2012). “Combining Creativity and Civilization: A
Natural Experiment in a General Education Course.” International Journal of Instructional Technology and
Distance Learning, 9, 33–41.
7. Grimshaw, Scott D. and Alexander, William P. (2011). “Markov Chain Models for Delin- quency: Transition
Matrix Estimation and Forecasts.” Applied Stochastic Models in Business and Industry, 27, 267–279.
8. Cornia, Gary C., Nelson, Ray D., Walter, Lawrence C., and Grimshaw, Scott D. (2010). “The Effect of Local
Option Sales Taxes on Local Sales.” Public Finance Review, 38, 659–681.
9. Blades, Natalie J., Grimshaw, Scott D., and Pendleton, Carly R. (2010). “A Simulation- Based Approach to
Evaluating Microarray Analyses.” Biostatistics, 11, 533–536.
10. Eddleman, James L., Sorber, Samual C., Morris, Thomas H., Grimshaw, Scott D., Dastrup, Emily, Christensen,
William F., Morris, Scott L. (2007). “Analysis of Fremont River strath terraces in the area of the Capitol Reef
National Park, Utah–Implications for fluvial landscape evolution and the role of climate forcing.” Central Utah–
Diverse Geology of a Dynamic Landscape, G.C. Willis, M.D. Hylland, D.L. Clark and T.C. Chidsey, Jr. (eds.).
Utah Geological Association, Salt Lake City, UT.
11. Grimshaw, Scott D., McDonald, James B., McQueen, Grant R. and Thorley, Steven R. (2005). “Testing for
Duration Dependence with Discrete Data.” Communications in Statistics: Simulation and Computation, 34, 451464.
12. Grimshaw, Scott D., Christensen, Howard B., Magleby, David B. and Patterson, Kelly D. (2004). “The Utah
Colleges Exit Poll: Learning by Doing.” Chance, 17, 32-38.
13. Alexander, William P., Grimshaw, Scott D., McQueen, Grant R., and Slade, Barrett A. (2002). “Some Loans Are
More Equal than Others: Third-Party Originations and Defaults in the Subprime Mortgage Industry.” Real Estate
Economics, 30, 667–697.
14. Grimshaw, Scott D., Collings, Bruce J., Larsen, Wayne A., and Hurt, Carolyn (2001). “Eliciting Factor Importance
in a Designed Experiment.” Technometrics, 43, 133-146. (2001 Wilcoxon Prize)
15. Grimshaw, Scott D., Whiting, David G., and Morris, Thomas H. (2001). “Likelihood Ratio Tests for a Mixture of
Two von Mises Distributions.” Biometrics, 57, 260-265.
16. Hilton, Sterling C., Grimshaw, Scott D., and Anderson, Genan T. (2001). “Statistics in Preschool.” The American
Statistician, 55, 332–336.
17. Grimshaw, Scott D., Bryce, G. Rex and Meade, David J. (2000). “Control Limits for Group Charts.” Quality
Engineering, 12, 177-184.
18. Grimshaw, Scott D., Shellman, Scott D., and Hurwitz, Arnon M. (1998). “Real-Time Process Monitoring for
Changing Inputs.” Technometrics, 40, 283–296.
19. Grimshaw, Scott D. (1998). “Treed Regression.” In Encyclopedia of Statistical Sciences Update, vol. 2, Samuel
Kotz, Compbell B. Read, and David L. Banks (eds.), 677–679. Wiley, New York.
20. Lawson, John L., Grimshaw, Scott D., and Burt, Jason (1998). “A Quantitative Method for Identifying Active
Contrasts in Unreplicated Factorial Designs Based on the Half- Normal Plot.” Computational Statistics and Data
Analysis, 26, 425–436.
21. Grimshaw, Scott D. and Alt, Frank B. (1997). “Control Charts for Quantile Function Values.” Journal of Quality
Technology, 29, 1–7.
22. Alexander, William P. and Grimshaw, Scott D. (1996). “Treed Regression.” The Journal of Computational and
Graphical Statistics, 5, 156–175.
194
23. Morris, Thomas H., Richmond, Dean R. and Grimshaw, Scott D. (1996). “Orientation of Dinosaur Bones in
Riverine Environments: Insights into Sedimentary Dynamics and Taphonomy.” The Continental Jurassic, Michael
Morales (ed.), 60, 521–530. Museum of Northern Arizona, Flagstaff, AZ.
24. Grimshaw, Scott D. (1993). “Investigating the Bias and MSE of Exceedance Based Tail Estimators for the Cauchy
Distribution.” In Proceedings of the Conference on Extreme Value Theory and Applications, vol. 3, 139–147.
NIST Special Publication 860.
25. Grimshaw, Scott D. (1993). “Computing Maximum Likelihood Estimates for the General- ized Pareto
Distribution.” Technometrics, 35, 185–191.
26. Jain, Kamlesh, Alt, Frank B. and Grimshaw, Scott D. (1993). “Multivariate Quality Con- trol – A Bayesian
Approach.” In ASQC Quality Congress Transactions, 645–651. American Society of Quality Control.
27. Grimshaw, Scott D. (1992). “Estimation of the Linear-plateau Segmented Regression Model in the Presence of
Measurement Error.” Communications in Statistics: Theory and Methods, 21(8), 2399-2413.
28. Grimshaw, Scott D. (1990). “A Unification of Tail Estimators.” Communications in Statis- tics: Theory and
Methods, 19(12), 4841-4857.
Non-Refereed:
1. Alt, Francis B. and Grimshaw, Scott D. (2013). “Quality Control,” in Encyclopedia of Operations Research &
Management Science 3rd ed., Gass, Saul I. and Fu, Michael C. (eds.). Springer, NY.
2. Alt, Francis B. and Grimshaw, Scott D. (2013). “Multivariate Quality Control,” in Ency- clopedia of Operations
Research & Management Science 3rd ed., Gass, Saul I. and Fu, Michael C. (eds.). Springer, NY.
3. Blades, Natalie J., Grimshaw, Scott D., and Scott, Del T. (2011). “Learning Outcomes for Undergraduate Statistics
Programs.” BYU Statistics Department Technical Report.
4. Grimshaw, Scott D. (2004). “Preschool Statistics.” The Statistics Teacher Network. Fall 2004.
5. Grimshaw, Scott D. and Fellingham, Gilbert W. (1998). “Statistical Development Using SAS / TOOLKIT
Software.” In Proceedings of the Twenty-Third Annual SAS Users Group International Conference, 1374–1377.
SAS Institute, Inc., Cary, NC.
6. Nelson, Todd R. and Grimshaw, Scott D. (1997). “SAS Interface for Run-to-Run Batch Process Monitoring
Using Real-Time Data.” In Proceedings of the Twenty-Second Annual SAS Users Group International
Conference, 1215–1219. SAS Institute, Inc., Cary, NC. (Best Contributed Paper)
7. Grimshaw, Scott D. (1995). Book Review of “An Introduction to the Bootstrap,” by Bradley Efron and Robert J.
Tibshirani, Technometrics, 37, 341.
8. Grimshaw, Scott D. and Alexander, William P. (1994). “Computational Efficiency in Treed Regression Using the
QR Decomposition,” BYU Statistics Department Technical Re- port.
9. Grimshaw, Scott D. (1991). “Calculating Maximum Likelihood Estimators for the Gen- eralized Pareto
Distribution.” In Computing Science and Statistics: Proceedings of the 23rd Symposium on the Interface, Elaine
M. Deramidas, ed., 616–619. Interface Foundation of North America. Fairfax Station, VA.
CURRENT RESEARCH INTERESTS:
Audience Measurement and Analytics; Control Charts; Data Mining; Statistical Computing.
Work In Progress:
• Jensen, Willis A., Espen, Ben, and Grimshaw, Scott D. “Nonlinear Profile Monitoring for Oven Temperature
Data.” Revise and Resumit to Journal of Quality Technology.
• Grimshaw, Scott D. “Incorporating Authentic Data Experiences Within Statistics Major Courses.” Under Review
to the American Statistician.
FUNDED RESEARCH:
• 2014–15 (not funded, submitted 2014). BYU Broadcasting. “TV Audience Analytics and Market Research.”
$24,000.
• 2014–15 (not funded, submitted 2014). National Institutes of Health. “Anthropome- try of Passive Wrist and
Forearm Stiffness.” $135,552. (P.I. with Steven K. Charles).
• 2013–14 BYU Broadcasting. “TV Audience Analytics and Market Research.” $18,000.
• 2013 (not funded, submitted 2013). Utah Valley University. “Philanthropic Wealth Screening and Predictive
Modeling.” $120,904.
• 2012 (not funded, submitted 2012). State of Utah, Administrative Office of the Courts. “Public Trust and
Confidence Survey.” $80,607. (P.I. with William F. Christensen).
• 2010–13 BYU Broadcasting. “Audience Measurement and Analytics.” $84,000.
• 2010-11 BYU Marriott School of Management (Gary C. Cornia). “Measuring the Im- pact of Wal-Mart Coming
to Sanpete County.” $12,000.
195
•
•
•
•
•
•
•
•
•
•
2009–11 (not funded, submitted 2009). National Science Foundation. “Focus on Fresh- men: Growing
Undergraduate Statistics Education.” $198,328. (P.I. with Natalie J. Blades and Del T. Scott).
2001–02 Manufactured Housing Division, Conseco Finance. “Dynamic Delinquency Movement.” $25,000.
Conseco Finance, Inc., St. Paul, MN.
1998–99 DuPont Education Aid Program Unrestricted Grant. “Experimental Design & Empirical Modeling.”
$20,000. DuPont, Inc., Wilmington, DE.
1997–98 DuPont Education Aid Program Unrestricted Grant. “Experimental Design & Empirical Modeling.”
$20,000. DuPont, Inc., Wilmington, DE.
1996–97 SEMATECH Sponsored Research Program No. 36082500-OP. “Methods for Modeling Real-time Data
from Inputs & Initial Conditions for use in the Real-time Process Monitor.” $17,500. SEMATECH, Inc., Austin,
TX.
1996–97 NBC Program Research, “Model Consistent Bias in Telephone Surveys that Gauge the Strength of
Programming Relative to Competition,” $15,000. NBC, Burbank, CA.
1995-96 SEMATECH Sponsored Research Program No. 75008932. “Development of Real-time Control
Methods: Real-time Process Monitor.” $17,020. SEMAT- ECH, Inc., Austin, TX.
1992 Office of Facilities Engineering, Fort Meade. “Measurement for Quality Im- provement for L-5 Managers.”
$3,500. Fort Meade, MD.
1990 Systems and Technology, Westinghouse. “Radar Processing Enhancement.” $5,000. With Frank B. Alt.
Westinghouse Electric, Corp., Baltimore, MD.
1990 General Research Board of Graduate Studies and Research Summer Research Award. “Tail Behavior
Parameters Estimated from the Sample Quantile Process.” $5,200. University of Maryland, College Park, MD.
PRESENTATIONS:
1. Invited, “Control Charts for Spatial Data,” INFORMS 2014, San Francisco, CA, October 2014.
2. “Choosing Most Popular NFL Games in a Local TV Market,” 2014 Joint Statistics Meetings, Boston, MA, August
2014.
3. “Final Four TV Audience,” Fall 2012 Utah ASA Chapter Meeting, Salt Lake City, UT, December 2012.
4. “Control Charts for Spatial Data,” 2012 Joint Statistics Meetings, San Diego, CA, August 2012.
5. “Efficient Computation of Generalized Median Estimators,” Statistics Department Seminar, Brigham Young
University, January 2011.
6. “Learning Outcomes and Assessment for Undergraduate Statistics Programs,” 2010 Joint Statistics Meetings,
Vancouver, BC, August 2010. “Control Charts for Spatial Data,” Virginia Tech, April 2009.
7. Invited Paper, “Control Charts for Spatial Data,” 2008 Fall Technical Conference, Phoenix, AZ, October 2008.
8. “Control Charts for Spatial Data,” Spring Research Conference for Industry & Technology, Atlanta, GA, May
2008.
9. Invited Poster, “Markov Chain Models for Delinquency: Transition Matrix Estimation and Forecasts,” 2003 Joint
Statistics Meetings, San Francisco, CA, August 2003.
10. Invited Paper, “Some Loans Are More Equal than Others: Third-Party Originations and Defaults in the Subprime
Mortgage Industry,” Interface ’03, Salt Lake City, UT, March 2003.
11. “Ancient Rivers, Dinosaur Bones, and Directional Data,” Brigham Young University — Idaho, October 2002.
12. “The Utah Colleges Exit Poll: Learning by Doing,” 2002 Joint Statistics Meetings, New York, NY, August 2002.
13. “Ancient Rivers, Dinosaur Bones, and Directional Data,” Statistics Department Seminar, Brigham Young
University, February 2002.
14. Invited Technometrics Session, “Eliciting Factor Importance in a Designed Experiment,” Spring Research
Conference on Statistics in Industry and Technology, Roanoke, VA, June 2001.
15. “Eliciting Factor Importance in a Designed Experiment,” Utah Chapter of the American Statistican Association,
Salt Lake City, UT, February 2001.
16. “Accuracy of 2000 Utah Colleges Exit Poll Predictions,” Math Department, Southern Utah University, Cedar City,
UT, December 2000.
17. “The Seven and a Half Laws of Statistical and Financial Success,” Statistics Department Seminar, Brigham Young
University, September 2000.
18. “Dynamic Delinquency Movement Matrix Loss Forecasting,” Delaware Chapter of the American Statistical
Association Annual Conference, April 2000.
19. “Dynamic Delinquency Movement Matrix Loss Forecasting,” College of Business and Man- agement, University
of Maryland, College Park, MD, April 2000.
20. “Regression Trees,” Structured Transactions and Analytical Research, First Union Capital Markets, Charlotte, NC,
November 1999.
21. “Regression Trees,” Department of Statistics Colloquium, University of South Carolina, Columbia, SC, October
1999.
196
22. “Process Improvement Using Real-time Data,” Spring Research Conference on Statistics in Industry and
Technology, Minneapolis, MN, June 1999.
23. “Process Improvement Using Real-time Data,” DuPont Experimental Design and Empirical Modeling
Conference, Wilmington, DE, March 1999.
24. Invited Seminar, “Eliciting Factor Importance in a Designed Experiment,” Institute for Improvement in Quality
and Productivity, University of Waterloo, October 1998.
25. Invited Discussant, “Utilizing Large Industrial Data Sets for Product and Process Quality Improvement,” 1998
Joint Statistics Meetings, Dallas, TX, August 1998.
26. “Prior Elicitation for Bayesian Analysis of Screening Designs,” Faculty Enrichment Seminar, Statistics
Department, Brigham Young University, June 1998.
27. “Examples of Prediction Using Stacked Treed Regressions,” Interface ’98, Minneapolis, MN, May 1998.
28. “Prior Elicitation for Bayesian Analysis of Screening Designs,” DuPont Quality Manage- ment & Technology
Center, Wilmington, DE, May 1998.
29. “Statistical Development Using SAS/TOOLKIT Software,” with Gilbert W. Fellingham, Twenty-Third Annual
SAS Users Group International Conference, Nashville, TN, March 1998.
30. Special Contributed Paper, “Run-to-Run Batch Process Monitoring Using Real-Time Data,” 1997 Joint Statistics
Meetings, Anaheim, CA, August 1997.
31. “SAS Interface for Run-to-Run Batch Process Monitoring Using Real-Time Data,” with Todd R. Nelson, TwentySecond Annual SAS Users Group International Conference, San Diego, CA, March 1997.
32. “Treed Regression,” Mathematics & Statistics Department Seminar, Utah State University, February 1997.
33. “Treed Regression,” Statistics Department Seminar, Texas A&M University, February 1997.
34. “RTPM-PRO Performance on Fault Detection and Classification Benchmarking Data,” SEMATECH, Austin,
TX, February 1997.
35. Invited Paper, “Regression Trees,” 1996 Joint Statistical Meetings, Chicago, IL, August 1996.
36. “Introduction to Quality Improvement & STAT 361,” AICHE Meeting, Brigham Young University, November
1995.
37. “Imposing Monotonicity in Treed Regression,” 1995 Joint Statistics Meetings, Orlando, FL, August 1995.
38. “The Bootstrap: a tutorial,” Statistics Department Seminar, Brigham Young University, November 1994.
39. “Treed Regression,” 1994 Joint Statistics Meetings, Toronto, CA, August 1994.
40. “Tail Estimation,” Statistics Department Seminar, Brigham Young University, October 1993.
41. “Quantile-based Control Charts,” Statistics Department Seminar, Brigham Young University, December 1992.
42. “An EWMA Using the Sample Generalized Variance for Monitoring a Multivariate Normal Process,” Quality
Assurance in the Government, Washington, DC, July 1992.
43. “Calculating Maximum Likelihood Estimators for the Generalized Pareto Distribution,” 23rd Symposium on the
Interface between Computing Science and Statistics, Seattle, WA, April 1991.
STUDENTS SUPERVISED
Year
Student
Role
1992 Fawzi Abdul-Wahab
Chair
(Ph.D. U. Maryland–College Park) “Optimal Quantile Based Control Charts for Location-Scale Alternatives”
1993 Kamlesh Jain
Chair
(Ph.D. U. Maryland–College Park) “A Bayesian Approach to Multivariate Quality Control”
1995 Shane Reese (MS BYU)
Chair
1996 Scott Shellman (MS BYU)
Chair
1996 Courtney Black (MS BYU)
Chair
1996 Greg Jones (MS BYU)
Member
1996 Xiaoying Xiao (MS BYU)
Member
1996 Todd Nelson (BS BYU)
Mentor
1997 Todd Nelson (MS BYU)
Chair
1997 Matthew Johnson (MS BYU)
Member
1997 David Dahl (BS BYU)
Mentor
1998 Chris Peterson (MS BYU)
Chair
1998 David Dahl (MS BYU)
Chair
1998 Carolyn Hurt (MS BYU)
Member
1998 Jared Christensen (BS BYU)
Mentor
(Undergraduate Award Recipient)
1999 Mike George (MS BYU)
Chair
1999 Rachelle Wilkinson (MS BYU)
Member
1999 Jamis Perrett (MS BYU)
Member
1999 Mike Richmond (MS BYU)
Member
2000 Stephanie Stanworth (MS BYU)
Chair
197
2000
2000
2000
2000
2000
2000
2000
2000
2001
2001
2002
2002
2003
2003
2003
2004
2004
2004
2005
2005
2005
2006
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
2009
2009
2010
Alexis Merrill (Exit Poll)
Betsy Lundy (Exit Poll)
Jeff Larsen (BS BYU)
Jana Sheppard (BS BYU)
Aimee Wahle (BS BYU)
Alvin Van Orden (BS BYU)
Melaney Slater (BS BYU)
Marcie Fillmore (BS BYU)
Hripsime Bandourian (MS BYU)
Saule Ahoshina (MS BYU)
Kenton Wride (MS BYU)
Alexis Merrill (MS BYU)
Sherstin Merx (BS BYU)
Jerry Butler (BS BYU)
Mark Lyman (BS BYU)
Nicole Smith (MS BYU)
Chris Green (MS BYU)
Betsy Lundy (MS BYU)
Emily Dastrup (MS BYU)
Mandy Woolstenhulme
(Ph.D. Exercise Science BYU)
James Eddleman (MS Geology BYU)
Michael Smith (MS BYU)
Ross Larsen (MS BYU)
Stephen Manortey (MS BYU)
Clint Stevenson (MS BYU)
John Ward (DNF)
Rebecca Monson Richardson (MS BYU)
April Logan (MS BYU)
Carly Pendleton (MS BYU)
Wendy Bunn (MS BYU)
Trenton Pulsipher (MS BYU)
Mark Lyman (MS BYU)
Natalie Johnson (MS BYU)
Kassie Fronczyk (MS BYU)
Matt Heaton (MS BYU)
Jared Collings (MS BYU)
Andrew Stacey (MS BYU)
Paul Johnson (MS BYU)
Emily Bell (MS BYU)
Scott Howard (MS BYU)
Todd Remund (MS BYU)
Greg Johnson (MS BYU)
Tom Stewart (MS BYU)
Jonathan Liljegren (MAcc BYU)
Zijun Dozier (MS Mathematics BYU)
Ben Hudson (MS Technology BYU)
Tomo Funai (BS BYU)
Angela Nelson (BS BYU)
Jared Geurts (BS BYU)
Claire Barker (BS BYU)
Brenda Ginos (MS BYU)
Claire Owen (MS BYU)
Andrea Thomas (MS BYU)
Mike Ulrich (MS BYU)
Enkhmart Dudleenamjil
(PhD Microbiology BYU)
Scott Morris (BS BYU)
Sarah Clark (BS BYU)
Rachel Teh (BS BYU)
James Hattaway (MS BYU)
Mentor
Mentor
Mentor
Mentor
Mentor
Mentor
Mentor
Mentor
Chair
Member
Chair
Member
Mentor
Mentor
Mentor
Member
Member
Member
Chair
Member
Member
Chair
Member
Member
Member
Chair
Chair
Member
Member
Member
Member
Member
Member
Member
Member
Member
Member
Member
Member
Chair
Member
Member
Member
Master’s Minor Member
Master’s Minor Member
Member
Mentor
Mentor
Mentor
Mentor
Chair
Member
Member
Member
Member
Mentor
IMPACT Mentor
IMPACT Mentor
Chair
198
2010
2010
2010
2010
2011
2012
2014
2014
Erika Hernandez (MS BYU)
Tommy Leininger (BS/MS BYU)
Sarah Wilde (BS BYU)
Rachel Teh (BS BYU)
Angela Nelson (BS/MS BYU)
Sarah Victors (MS BYU)
Paul Sabin (BS/MS BYU)
Andrew Brock (MS BYU)
Member
Member
IMPACT Mentor
IMPACT Mentor
Chair
Chair
Chair
Chair
COURSES TAUGHT AT BRIGHAM YOUNG UNIVERSITY
Graduate Courses
• Stat 535: Applied Linear Models. (1 time, last taught Fall 2013)
• Stat 536: Modern Regression Methods. (8 times, last taught Winter 2013) Stat 624: Statistical Computation. (2
times, last taught Fall 2008)
• Stat 525: Statistical Inference. (1 time, last taught Fall 1998) Stat 536: Regression Analysis. (3 times, last taught Fall
1997) Majors Courses
• Stat 340: Introduction to Regression. (1 time, last taught Fall 2014)
• Stat 435: Nonparametric Statistical Methods. (4 times, last taught Fall 2014) Stat 340: Inference. (1 time, last
taught Winter 2014)
• Stat 290: Communication of Statistical Results. (5 times, last taught Winter 2013) Stat 462: Quality Control &
Industrial Statistics. (5 times, last taught Winter 2007) Stat 336: Statistical Methods I. (10 times, last taught Winter
2005)
• Stat 469: Applied Time Series & Forecasting. (5 times, last taught Fall 2005) Stat 334: Methods of Survey
Sampling. (2 times, last taught Winter 2001)
• Stat 421: Probability and Distribution Theory. (2 times, last taught Winter 1997)
Undergraduate Service Courses
• Stat 121: Principles of Statistics. (1 time, last taught Fall 2013)
• Stat 201: Statistics for Engineers and Scientists. (4 times, last taught Fall 2013) Stat 332: Quality Improvement for
Industry. (4 times, last taught Summer 2010) Stat 361: Quality Improvement for Industry. (5 times, last taught
Spring 2003) Stat 221/222: Principles of Statistics. (7 times, last taught Winter 1999)
• Stat 321: Elements of Mathematical Statistics. (2 times, last taught Winter 1993)
Graduate Service Courses
• Stat 510: Introduction to Statistics for Graduate Students. (1 time, last taught Winter 2008)
• Stat 512: Statistical Methods for Research 2. (2 times, last taught Winter 2003) Stat 532: Quality Improvement for
Engineering. (1 time, last taught Winter 1998)
199
APPENDIX J.
Faculty Postdoctoral Researchers, 2009-2014
Carroll, Raymond
Assaad, Houssein (Research Assistant Professor, STATA Corporation)
Bhadra, Anindya (Assistant Professor, Purdue University)
Bliznyuk, Nikolay (Assistant Professor, University of Florida)
Garcia, Tanya (Assistant Professor, Texas A&M School of Public Health)
Hernandez-Magallanes, Irma (Postdoctoral Research Associate, Texas A&M Department of Statistics)
Joseph, Maria (Senior Statistician, General Dynamics Information Technology)
Kaprievitch, Yuliya (Lecturer, University of Tasmania)
Lee, Myoungji (Manager, Enterprise Model Validation Group, American Express)
Li, Haocheng (Affiliation Unknown)
Martinez, Josue (Affiliation Unknown)
Potgieter, Cornelius (Assistant Professor, University of Johannesburg)
Ryu, Duchwan (Assistant Professor, Northern Illinois University)
Maadooliat, Mehdi (Assistant Professor, Marquette University)
McLean Mathew (Research Assistant Professor, Texas A&M Department of Statistics)
Mohsenizadeh, Daniel (Research Assistant Professor, Texas A&M Electrical & Computer Engineering)
Murphy, Mary (Affiliation Unknown)
Tekwe, Carmen (Assistant Professor, Texas A&M School of Public Health)
Wei, Jiawei (Statistical Methodologist, Novartis)
Xu, Ganggang (Assistant Professor, Binghamton University)
Zhang, Xinyu (Affiliation Unknown)
Zoh, Roger (Research Assistant Professor, Texas A&M School of Public Health)
Zollanvari, Amin (Assistant Professor, Electronic Engineering Istanbul Kemerburgaz University)
Zorych, Ivan (Columbia University)
IAMCS/KAUST (Raymond Carroll)
Copeland, Dylan (Research Scientist at Global Geophysical Services)
Jin, Bangti (Assistant Professor, University of California, Riverside)
Li, Xiangfang (Assistant Professor, Prairie View A&M University)
McClarren, Ryan (Assistant Professor, Texas A&M Nuclear Engineering)
Oancea, Cosmin (Assistant Professor, University of Copenhagen)
Qian, Xiaoning (Assistant Professor, University of South Florida)
Pauletti, Miguel S. (Affiliation Unknown)
Schwartz, Scott (Research Associate, University of Texas, Austin)
Simeonova, Lyubima (Process Control Engineer, IM Flash Technologies)
Steinhauer, Dustin (Instructional Assistant Professor, Texas A&M Mathematics)
Wang, Jue (Senior Research Scientist, Adobe Research)
Wang, Xueying (Assistant Professor, Washington State University)
Zedler, Sarah (Research Associate, University of Texas at Austin Institute for Geophysics)
Huang, Jianhua
Huang, Wei (Affiliation Unknown)
Johnson, Valen
Breda, Ardala (Postdoctoral Research Associate, Texas A&M Department of Statistics, begin 2015)
Pan, Xuedong (Postdoctoral Research Associate, Texas A&M Department of Statistics, begin 2015)
Reed, Katherine (Postdoctoral Research Associate, Texas A&M Department of Statistics)
Sanyal, Nilotpal (Postdoctoral Research Associate, Texas A&M Department of Statistics, begin 2015)
Yajima, Ayako (Postdoctoral Research Associate, Texas A&M Department of Statistics, begin 2015)
200
Mallick, Bani
Bhadra, Anindya (Assistant Professor, Purdue University)
Chakraborty, Avishek (Assistant Professor, University of Arkansas)
Chatterjee, Arindam (Assistant Professor, Stat-Math Unit, Indian Statistical Institute)
De, Swarup (Analytical Consultant, SAS)
Dhavala, Soma (Associate Research Scientist, Dow AgroSciences, LLC)
Guha, Nilabja (Postdoctoral Research Associate, Texas A&M Department of Statistics)
Kundu, Suprateek (Assistant Professor, Emory University)
Zoh, Roger (Research Assistant Professor, Texas A&M School of Public Health)
Sheather, Simon
Broglio, Kristine (Statistical Scientist, Berry Consultants)
201
APPENDIX K.
Texas A&M University
Department of Statistics
ByLaws
Introduction
The faculty of the Department of Statistics has as its primary duty to advance the discipline of statistics through teaching,
research, service, and consulting. This should be accomplished in an atmosphere of collegiality and cooperation. Each
faculty member has a responsibility in furthering the academic goals of the department and in maintaining the excellence
of the department. This set of bylaws outlines the manner in which the faculty can achieve these goals.
The Department of Statistics shall be governed by these bylaws, which in turn are governed by policies of the Texas
A&M University System, Texas A&M University, and the College of Science. The policies and procedures described
in this document are based on the policy statements of the Texas A&M System, Texas A&M University, and the
College of Science when appropriate. When those rules and policies change, the Department shall abide by those
new rules and policies until the Department can amend these bylaws to reflect the changes.
A major goal of the bylaws is to bring order to the functioning of the Department by defining the rights and duties of
department members. These bylaws reflect the principle that the responsibility for effective governance rests with both
the faculty and the Department Head. Furthermore, effective governance depends on the exercise of responsible
leadership by the faculty and the Department Head in their respective roles. The rules and responsibilities described
in these bylaws shall be implemented with strict adherence to academic freedom, due process, and equal opportunity.
I.
Faculty Organization
A. Membership of the Faculty of the Department of Statistics
1. All persons holding half-time or greater academic appointments in the Department of Statistics
at the ranks of Distinguished Professor, Professor, Associate Professor, Assistant Professor,
Executive Professor, Senior Professor, Senior Associate Professor, Instructional Professor,
Instructional Associate Professor, Instructional Assistant Professor, Senior Lecturer, and Lecturer
are considered to be voting members of the faculty of the Department of Statistics at Texas A&M
University (hereinafter, Department). A full-time appointment is defined as 100% during the nine
month academic year. The descriptions of all faculty categories and ranks are contained in the
document, “Texas A&M University Guidelines to Faculty Titles.”
2. Faculty members holding joint appointments or adjunct appointments in the Department, visiting
faculty, and part-time faculty are welcome to attend faculty meetings but cannot vote on
Departmental issues. A vote on tenure or promotion matters is restricted to appointments to be
made at an equivalent or lower rank than the voting faculty member. Faculty ranks for voting
purposes are as follows: Professor, Associate Professor, Assistant Professor, Executive Professor,
Senior Professor, Senior Associate Professor, Instructional Professor, Instructional Associate
Professor, Instructional Assistant Professor, Senior Lecturer, Lecturer.
B. Administrative Positions in the Department
a. Department Head
The Department Head is the administrative and executive officer of the Department and serves
as the spokesperson to the University administration and communities outside of the University.
b. Term of Office
The term of office of the Department Head shall be four years, and is renewable. The
Department Head shall be reviewed in the third year of the term according to the procedures
202
established by the College of Science for all department heads within the College of Science.
c. Procedures for Selection of the Department Head
i. The Dean will establish a search committee following consultation with the faculty of the
Department and will appoint the chair of the committee, who often is a faculty member
outside of the Department but within the College of Science. A majority of the committee
should be elected by the faculty of the Department. The Dean may appoint additional
members to the committee.
ii. The search committee will advertise the position, will review all applicants and nominations,
and will make recommendations to the faculty of the Department regarding their preferred
candidate(s). A faculty meeting will be held to discuss the qualifications of the recommended
candidates. After the faculty meeting, the committee will send the Dean a list of
candidates which the committee has identified to invite for an interview. After receiving the
Dean’s approval, the candidates will be invited for an interview. Pursuant to the Texas Open
Records Act, all non-confidential material pertinent to applicants and nominations will be
available to the entire faculty for review.
iii. Following a written or online ballot vote of the faculty, the candidate(s) receiving a majority
affirmative support will be recommended to the Dean. A ranking of the candidates may also
be sent to the Dean if the faculty or search committee so desires. If the vote of the faculty
as a whole differs from the opinion of the search committee, that information will also be
reported to the Dean, along with the recorded vote. The Dean will select and appoint the
Department Head.
iv. See University Document 12.99.99.M6 - Faculty Participation in the Selection, Evaluation, and
Retention of Department Heads - for more details.
d. Duties of the Department Head
The Department Head, through direct action or delegation, shall:
i. In consultation with the Advisory Committee and appropriate Department committees,
formulate and implement policies of the Department;
ii. Consult regularly with Departmental committee chairs;
iii. Preside at Departmental faculty meetings and ensure that accurate minutes of the meetings
are preserved and that a summary of the minutes is distributed to the faculty at a reasonable
time following the meeting;
iv. Formulate and manage the Departmental budget;
v. Manage office operations;
vi. Evaluate faculty and staff annually;
vii. Encourage faculty development;
viii. Carry on departmental correspondence;
ix. Resolve student complaints and potential conflicts;
x. Serve as the Department’s representative to ASA, SRCOS and COTS;
xi. Seek advice from individual faculty members, from Departmental committees, and from
the faculty as a whole;
xii. Be an ex officio member of all duly constituted Departmental committees.
e. Authority of the Department Head
i. The Department Head appoints the chairs of all Departmental commit- tees.
203
ii. It is expected that the Department Head will usually support the decisions of the committees
and the faculty. If the Department Head is unable to support a recommendation made through
usual procedures, the Department Head should, in a timely fashion, give a written explanation
to the faculty or to the appropriate committee. In cases of disagreement, the Department
Head should include relevant votes of committees and the vote of the faculty when reporting
to the College of Science and University.
iii. The Department Head, serving as the principal financial officer of the Department, shall:
1. Supervise receipt and expenditure of all monies;
2. Prepare an annual operating budget.
iv. The Department Head, in conjunction with appropriate committees, shall supervise and
coordinate the recruiting of new faculty members.
v. The Department Head shall make recommendations for faculty salary increases to the
Dean.
vi. The Department Head shall be responsible for initiating meetings of the Promotion and
Tenure Committee in order to ensure timely recommendations for promotion and tenure
decisions in the Department and at the College level.
2. Associate Department Head
a. The appointment of the Associate Department Head is recommended to the Dean by the
Department Head, in conjunction with the Advisory committee.
b. The term of the office of the Associate Department Head shall be four years, renewable at the
discretion of the Department Head.
c. The duties of the Associate Department Head include:
i. Serve in the capacity of the Department Head whenever the Department Head is
unavailable;
ii. Serve as the chair of the Advisory committee;
iii. Serve on the Student Evaluation committee;
iv. Administer teaching assistantships;
v. Administer MS Diagnostic Exam and PhD Qualifying Exam;
vi. Assign teaching schedules;
vii. Develop and coordinate summer internships;
viii. Function in the capacity of the Department Head in all matters delegated by the Department
Head.
3. Academic Director of Online Programs
a. Is appointed by the Department Head.
b. The duties of the Academic Director of Online Programs include:
i. Prepare an annual budget for the online program;
ii. Chair the online M.S. admissions committee;
iii. Develop marketing plans for the online program;
iv. Supervise the online program’s staff;
v. Develop projects for online M.S. students;
vi. Be responsible for new initiatives in the online program.
204
4. Academic Director of M.S. Analytics
a. Is appointed by the Department Head.
b. The duties of the Academic Director of M.S. Analytics include:
i. Oversee curriculum development and faculty teaching;
ii. Manage all administrative aspects of the program: budgeting, strategic enrollment
management, all student life cycle issues, and alumni affairs;
iii. Faculty recruitment, hiring, and ongoing management;
iv. Instructional support for faculty;
v. Student advising;
vi. Chair the admissions committee;
vii. Interface with external organizations;
viii. Plan and implement specific co-curricular and extra-curricular events as needed.
5. Graduate Advisor
a. Is appointed by the Department Head.
b. Chairs the Graduate Curriculum committee.
c. Chairs the Graduate Student Admissions committee.
d. The duties of the Graduate Advisor include:
i. Advise graduate students;
ii. Serve on university committees associated with graduate admissions, ad- vising, and
fellowships;
iii. Administer graduate student fellowships;
iv. Conduct an annual evaluation of graduate students’ advancement to their Ph.D.;
v. Function in the capacity of the Department Head in all matters delegated by the Department
Head.
6. Undergraduate Advisor
a. Is appointed by the Department Head.
b. Chairs the Undergraduate Curriculum committee.
c. Chairs the Undergraduate Student Admissions committee.
d. The duties of the Undergraduate Advisor include:
i. Advise undergraduate students;
ii. Serve on university committees associated with undergraduate admissions, advising, and
fellowships;
iii. Administer undergraduate scholarships;
iv. Function in the capacity of the Department Head in all matters delegated by the Department
Head.
C. Faculty Meetings
1. There will be at least six regular meetings of the Department faculty during the academic year.
These regular meetings of the Department faculty shall be held at even intervals during the
academic year. The Department Head shall distribute to the faculty an agenda for each regular
meeting at least two days prior to the meeting.
2. The Department Head, or designee, shall preside at each meeting of the Department faculty.
3. Guests may be invited to meetings of the Department faculty by the Department Head or by a
member of the Department faculty with concurrence of the Department Head.
4. The Department Head will ensure that accurate minutes of the meetings are preserved and that
205
a summary of the minutes is distributed to the faculty at a reasonable time following the meeting.
II. Faculty
A. New Faculty
1. Priorities for new faculty recruitment shall be discussed during a meeting of the Department
faculty.
2. Tenured/tenure-track faculty positions shall be advertised nationally. Applicants shall be
requested to supply a professional vita, along with a statement of research interests and teaching
philosophy, and at least three letters of recommendation. All applicants received shall be reviewed
by the Department Faculty Recruitment Committee and this committee will select a subset of
all applicants for consideration by the faculty during a Department faculty meeting. The faculty
shall then select which applicants to be invited for an on campus interview.
3. A Department faculty meeting shall be held to discuss the qualifications of all applicants making
a campus visit. A faculty vote to select which applicant(s) will receive a position offer will be
conducted after the discussion.
4. Appointments at the rank of Lecturer may be made by the Department Head with the
concurrence of the Advisory Committee.
5. Appointments at the rank of Senior Professor, Senior Associate Professor, Instructional
Professor, Instructional Associate Professor, Instructional Assistant Professor, and Senior
Lecturer may be made by the Department Head upon recommendation of the P&T Committee.
6. Adjunct Faculty: Any voting faculty member may propose an adjunct faculty appointment. The
candidate’s curriculum vitae must be distributed to the faculty. A discussion and vote on granting
of the adjunct position will take place at the first faculty meeting following the distribution of the
cv.
B. Visiting Faculty Appointments
1. Any member of the Faculty may recommend the appointment of visiting faculty members at the
rank of Visiting Professor, Visiting Associate Professor, or Visiting Assistant Professor. The
purpose of such appointments shall be to bring within the Department for a limited period of
time scientists whose interactions with the faculty or students of the Department can be expected
to benefit the Department with respect to research and/or teaching.
2. Visiting faculty appointments shall be for a period of no more than one year.
3. The decision on offering a visiting faculty position shall be made by the Department Head.
C. Faculty Leaves of Absence
1. Applications for sabbatical leaves shall ordinarily be submitted to the Department Head not
later than nine months before the proposed leave.
2. A leave of absence shall be for a period of no more than one year.
3. If the sabbatical is for one semester, then the faculty member’s teaching load will be one course
during the second semester of the sabbatical year.
4. Requests for short term leaves during a period in which classes are in session must be submitted to
the Department Head.
5. Texas A&M University’s parental teaching load redistribution guideline is designed to provide
flexibility in teaching obligations of faculty members who are the primary care givers to their
newborn infant, or to their newly adopted infant or child. The Department Head will work with
faculty to arrange one/ two semester(s) of relief from formal classroom teaching or other timerigid duties for the birth or adoption of a child for any eligible faculty member. Also, faculty
may be granted leave in accordance with the Family and Medical Leave Act or any currently
applicable state or federal law.
206
D. Instructional Faculty and Lecturers
An instructional faculty member (i.e., instructional professor, instructional associate professor,
instructional assistant professor) or lecturer is a non-tenure track faculty member whose primary function
is classroom teaching. The appointment of an instructional faculty member or lecturer is generally
restricted to persons who possess a Ph.D. in statistics or related fields but in special circumstances, an
M.S. will be acceptable. The term of initial appointment is one year; subsequent one-year appointments
may be offered. Instructional faculty members and lecturers will be recruited by an open announcement
of the position. The Department Head shall decide on whether to hire an instructional faculty member
or lecturer.
There will not be a faculty vote on the hiring of instructional faculty members or lecturers.
1. The title of Instructional Professor, Instructional Associate Professor, Instructional Assistant
Professor and Senior Lecturer is to be used for faculty who meet the criteria of Lecturer, and
who have at least fi e years of experience as a Lecturer or its equivalent. Initial appointment to
these ranks requires a recommendation of the Promotion and Tenure Committee, the Department
Head, and approval of the Dean.
2. Instructional faculty members and Senior Lecturers will have annual appointments for at least the
first three years, but will always receive 12 months’ notice if they are not to be reappointed.
3. Status, Expectations, and Professional Development
a. Instructional faculty members and lecturers are members of the Department faculty and will
be afforded the respect and status comparable to that of tenured and tenure track faculty.
b. Instructional faculty members and lecturers will be included in all Depart- mental academic
affairs, including faculty meetings, committee meetings, and curriculum development.
c. Instructional faculty members and lecturers will be provided office space and the computer
facilities necessary to fulfill their teaching responsibilities.
d. Instructional faculty members and lecturers will be encouraged to initiate and/or participate in
scholarly activities associated with all aspects of statistical education.
e. Instructional faculty members and lecturers may apply for membership on the graduate
faculty in accordance with OGAPS guidelines. An instructional faculty member or lecturer
may serve as the chair of an MS student’s committee but not as the chair of a Ph.D. student’s
committee.
4. Annual Review
a. The performance of all Instructional faculty members and lecturers will be reviewed by the
Department Head annually.
b. Performance criteria will be based on teaching and related activities, with additional recognition
given to publications and service.
c. Based on annual reviews, instructional faculty members and lecturers may be recommended
to the P&T Committee for promotion to Senior Lecturer, Instructional Assistant Professor,
Instructional Associate Professor, or Instructional Professor.
III. Teaching
A. Academic Year Teaching Assignments
1. The teaching load for all tenured, tenure-track faculty will be three courses during the academic
year during that period of their career when they are actively involved in research.
2. If a faculty member’s research effort is deemed by the Department Head to be inactive, the
Department Head will modify the duties of the faculty member by increasing the teaching load
to more than three courses per academic year and/or ask the faculty member to direct the M.S.
projects for Online Learning students. Faculty members may initiate a discussion with the
207
3.
4.
5.
6.
7.
Department Head concerning a change in title to Senior Professor or Senior Associate
Professor if they do not intend to increase their research productivity. A change in title
requires the Dean of Faculty’s approval.
Other exceptions to the standard teaching assignment are a two course per academic year
assignment for Distinguished Professors, Associate Department Head, Academic Director of
Online Programs, and Graduate Advisor. The Department Head is not expected to have
teaching responsibility but may teach at his/her discretion. The Department Head, at his or
her discretion, may also reduce the teaching load of regular faculty members by one course for
exemplary service in attracting external grant funding, for the publication of seminal research, or
for meritorious service as the chair of a departmental committee.
Senior Lecturers and Lecturers will teach three or more courses per semester during the academic
year.
The Department Head, as part of the recruitment package, may reduce the teaching load for
newly hired faculty. For example, Assistant Professors during the first two years of their
appointment have a teaching load of two courses per academic year.
Faculty members may decide to reduce their teaching load by using grant money to buy out
of a course. The rate to buy out a course for a faculty member who is the P.I. on a grant
is the smaller of $28,500 and 2 months salary. The cost of a non-P.I. is the smaller of $28,500
and 3 months salary. This rate will be adjusted annually by the Department Head. The
faculty member shall notify the Associate Department Head at least two months prior to
the beginning of the semester so that adjustments may be made to the teaching assignments.
To facilitate preparation of course materials, teaching assignments shall normally be determined
three months in advance of the assignment.
B. Departmental Summer Appointments
1. Prospective summer teaching positions shall be advertised to the Department faculty by the
Associate Department Head.
2. Department faculty members shall apply for summer teaching appointments in writing to the
Associate Department Head, in accordance with a time schedule announced by the Department
Head.
3. Summer teaching appointments shall be made by the Associate Department Head. Priority in
summer teaching opportunities will be given fi to Department faculty.
4. Certain activities such as the M.S. Diagnostic Examination and Ph.D. Qualifying Examination
will require faculty participation during the summer. Faculty members who can comply without
serious inconvenience may be called upon to perform such duties without additional compensation.
C. Distance Learning Teaching Assignments
1. The Department teaches a number of distance learning courses. The Distance Learning program
provides a stipend to the instructor for teaching the two extra sections of the assigned course. This
stipend is deposited into an account to be used by the instructor for professional development.
2. The Department offers a repeat of distance courses taught in the previous semester. The
instructors for these courses do not provide the lecture for the course but create homework
assignments, exams, conduct a weekly Q&A session, and monitor the discussion board. These
duties are referred to as “minding the course”. The Distance Learning program provides one
month of summer salary for minding a course. The selection of faculty to mind a course is
made by the Associate Department Head and is an additional course which does not count
towards the instructors three course teaching assignment.
D. Analytics Teaching Assignments
1. In conjunction with the Mays Business School, the Department offers a M.S. degree in Analytics.
The courses are taught in Houston and online. The instructors for these courses are recruited
208
by the Academic Director of Online Programs. The instructors are paid a stipend which is in
addition to their nine month salary.
2. The teaching of an Analytics course does not count towards the faculty member’s teaching
assignment.
IV. Research Advising
A. Selection of Graduate Research Advisors
1. The selection of a graduate research advisor is one of the most important decisions that a
graduate student will make. To assist students in making the decision, the faculty are
encouraged to participate in Brown Bag seminars sponsored by the Statistics Graduate
Student Association. Another avenue to assist the graduate students and the faculty in
obtaining a productive matching of graduate student with advisor is the teaching of Special
Topics courses. In these STAT 689 courses the student and faculty member are able to assess
the capability of the student to conduct research and for the student to become familiar with
the research interests of the faculty member. The faculty are encouraged to have a current
webpage populated with information detailing their research program. The faculty are
encouraged to present seminar talks in our department to expose interested students to the
faculty member’s research interests.
2. OGAPS allows an Adjunct Professor in the Department of Statistics and any member of the
graduate faculty at Texas A&M University to serve as a co- chair of M.S. and Ph.D.
committees. The Chair of these committees must be a faculty member in the Department of
Statistics.
3. The selection of a research advisor is a serious matter and usually it is expected that a student
will remain with his/her chosen advisor for the duration of the degree program. However, in the
rare case that a student may wish to change advisor, a petition in writing by the student to the
Graduate Advisor shall be composed. The Graduate Advisor shall then provide the student
with advice on making the change. The student is expected to select a new advisor prior to
the start of the following semester.
B. Postdoctoral Appointments
All appointments at the postdoctoral level must be approved by the Department Head,
regardless of the funding source. This requirement is normally satisfied via the employment
documents which bear the Department Head’s signature. Appointment periods must be stated
clearly on the appropriate employment documents.
C. Research Assistantships
Faculty wanting to support a research assistant shall notify the Associate Department Head at
least two months prior to the beginning of the semester in which the support is provided if the
proposed student is currently being supported as a teaching assistant (TA) or technology
teaching assistant (TTA).
V. Committees
A. General Procedures
1. Service on Departmental committees is considered a normal part of each faculty member’s duties.
All faculty members are encouraged to raise issues to be considered by any of the Department’s
committees. Meetings of committees will be held only when a majority of the voting members of
the committee are present. Unless otherwise stated, all committee members serve in a voting
capacity.
2. The agenda for each meeting will be determined by the committee chair and a copy of the agenda
should be distributed to members at least one day in advance of the meeting.
209
3. Except as otherwise noted, all committees will establish their own procedures, provided that the
following conditions are met:
a. Members of the Department concerned with an issue relevant to the committee shall be
afforded an opportunity to present their views during a scheduled meeting of the committee.
b. Any faculty member of the Department may make proposals to the committee in writing.
Such proposals will normally be given consideration within two months.
c. Each committee will establish procedures for receiving and considering proposals from
undergraduate and graduate students as appropriate.
d. Some committees include student representation. During discussions involving the evaluation
of a particular student or faculty member, the student representative must be excused from
the room in which the meeting is being held.
B. Departmental Committees
Unless otherwise stated in this document, departmental committees will be selected by the
Department Head, with the proviso that at least one member of the committee shall serve a twoyear term in order to provide continuity to the committee’s operations.
Advisory Committee - The purpose of the Advisory Committee is to re- view major
departmental actions and make recommendations to the Department Head, and to serve as a
resource for long-range planning and policy issues related to all activities, other than curriculum,
in the Department.
Awards Committee - Solicits and reviews nominations of Department faculty members for
College and University awards, and for professional society awards. Reviews applications and
nominations for awards to Department graduate students.
Colloquia-Special Events Committee - Organizes and coordinates departmental colloquium
and special seminars.
Endowed Positions Committee - Reviews applications and nominations for endowed
positions
Faculty Recruitment Committee - Reviews applications and nominations for faculty positions
Graduate Admissions Committee - Reviews academic records and qualifications of
prospective graduate students; Recommends to the Department Head students for admission.
Graduate Curriculum Committee - Establishes and reviews Departmental standards related
to the graduate course requirements; review Depart- mental policies related to M.S. Diagnostic
exam, Ph.D. Qualifying exam, and Ph.D. Preliminary exam; reviews faculty proposals for new
graduate courses.
Graduate Service Committee - Periodically reviews the syllabi for graduate service courses.
Graduate Student Evaluation Committee - Constructs the Ph.D. Qualifying Exam which will
be administered annually, two weeks after the end of Spring Semester. Reviews academic records
and performance on the Ph.D. Qualifying Exam and makes a recommendation to the
Department Faculty on which students shall be allowed to continue in the Ph.D. program.
To facilitate student advising, the Graduate Advisor shall not be a member of this committee.
Post-Tenure Review Committee - Reviews instructional and research performance and
professional activities of Full Professors; provides input to the Department Head on the
performance of tenured Full Professors.
Promotion and Tenure Committee - Reviews instructional and research performance and
210
professional activities of Lecturers, Assistant and Associate Professors; advises Department Head
on promotion, tenure, and appointment recommendations.
Undergraduate Curriculum Committee - Reviews curricula and requirements of
undergraduate majors; plans modifications and improvements to the undergraduate program.
C. Advisory Committee (AC)
1. The AC consists of eight members with at least one Lecturer, Assistant Professor, and Associate
Professor serving on the committee. The chair of the AC is the Associate Department Head.
The AC’s members are either elected by the faculty or appointed by the Department Head.
2. The AC will establish a regular time for its meeting. The agenda for these meetings will be
determined by the chair of the AC and will be posted several days prior to the meeting. It is
expected that the AC will meet every month during the academic year and occasionally during
the summer months as needed.
3. The purpose of the AC is to advise the Department Head and to serve as the Department
Head’s resource for long range planning and policy issues. The AC will represent the Department
as a whole, keeping the Department Head informed of both current problems confronting the
faculty as well as discussing directions for future development of the Department.
D. Post-Tenure Review (PTR) and the PTR Committee
At least once every six years, an evaluation of each tenured faculty member is conducted by the
Department of Statistics. This review is in addition to the annual reviews performed by the
Department Head. The performance of each tenured faculty member will be evaluated with respect
to teaching, research, and service.
1. Membership of the PTR Committee will consist of three elected members by vote of the
Department’s Full Professors and two members appointed by the Department Head.
2. The duties of the PTR Committee are as follows:
a. Each tenured professor will be reviewed by the PTR Committee no less than once every six
years.
b. The PTR Committee will base their review on materials submitted by the reviewed faculty
member and materials from the annual faculty reviews. The faculty member undergoing review
may include materials other than those listed.
c. The PTR Committee will recommend to the Department Head an evaluation of Satisfactory
or Unsatisfactory for each tenured professor along with supporting documentation of their
assessment. The assessment will be based on the criteria listed in Section VI.
d. A vote of all fi e members is required.
3. If the report from the PTR Committee fi the faculty member at an unsatisfactory level in
performance, a Professional Review will be initiated. The details for the Professional Review
are in the Texas A&M University Post- Tenure Review document, 12.06.99.M0.01.
4. If a faculty member receives an unsatisfactory report from the annual evaluation by the Department
Head for three consecutive years, the faculty member will be subject to the Professional Review as
specified in the Texas A&M University Post-Tenure Review document, 12.06.99.M0.01.
E. Promotion and Tenure Committee (P&T)
1. The procedural rules for the P&T Committee are detailed in the document, Promotion, Tenure, and
Annual Review Guidelines, Department of Statistics, Texas A&M University, August 2012.
2. Membership consists of three faculty members appointed by the Department Head; three Full
Professors elected by a majority vote of the entire tenured and tenure-track faculty; and one
Associate Professor elected by a vote of the Assistant and Associate Professors. Elections are held
during the fi week of February. The P&T Committee chair is appointed by the Department Head.
Faculty who have served three consecutive years will be removed from the ballot for the following
two years.
211
3. The duties of the P&T Committee are as follows:
a. Each spring the P&T Committee prepares a written evaluation of the progress of each of
the non-tenured faculty members in tenure-track positions.
b. A third-year review will be prepared for all non-tenured Assistant Professors in a tenure-track
position.
c. Each spring the P&T Committee prepares a written evaluation of the progress of each of
the Associate Professors towards promotion to Full Professor.
d. The Department Head does not participate in making the written evaluation but the
Department Head will meet with each of the Assistant and Associate Professors to review
the P&T Committee’s evaluation.
e. The P&T Committee prepares a committee discussion report and recommendations for each
candidate for promotion and/or tenure. The report shall follow the guidelines from the Dean
of Faculties.
f. The P&T Committee shall prepare guidelines on the procedures required of candidates for
tenure and promotion. These guidelines shall be distributed to all faculty holding the rank
of Lecturer, Assistant Professor, and Associate Professor.
g. The P&T Committee will consider for emeritus status every individual who, at the time of
retirement, holds a tenured appointment in the department and has served the university at
least ten years unless the in faculty member requests in writing that he/she not be so
considered. Individuals who are non-tenured or who have served less than ten years may also be
considered.
4. A vote of all seven members is required for promotion and tenure decisions.
VI. Faculty Evaluation
The evaluation of faculty in the Department of Statistics is the responsibility of the Department Head.
The Department Head solicits advice from Departmental committees in the evaluation of the
performance of the faculty.
A. Procedures
1. Annual Review: Each year the department, in accordance with the University Statement on
Academic Freedom, Responsibility, Tenure, and Promotion (SAFRT), will carry out an annual
review of all faculty in the ranks of Lecturer, Senior Lecturer, Instructional Assistant Professor,
Instructional Associate Professor, Instructional Professor, Senior Associate Professor, Senior Full
Professor, Assistant Professor, Associate Professor, and Full Professor. The review will follow the
form contained in the SAFRT with the following clarifications:
i. The criteria to be used in the evaluation process are contained in Section B.
ii. The annual review will take place during the Spring semester.
iii. The faculty shall submit the department’s Annual Report Form detailing their activities for the
previous calendar year with respect to research, teaching, and service.
iv. The Department Head shall provide every faculty member a written report detailing the
Department Head’s assessment of their performance in the areas of teaching, research, and
service.
v. The Department Head will also meet with each Assistant Professor and Associate Professor
to discuss their performance and progress towards tenure and promotion. Any of the
remaining faculty may request a meeting with the Department Head to discuss the written
summary of their performance.
vi. If a faculty member wishes to disagree with anything contained in the Department Head’s
written report, he/she may append a written comment to the report.
vii. If a faculty member’s annual evaluation by the Department Head results in an Unsatisfactory
212
for three consecutive years, the faculty member will be subject to the Professional Review
as specified in the Texas A&M University Post-Tenure Review document, 12.06.99.M0.01.
2. Promotion and Tenure: The P&T Committee is responsible for advising the Department Head
on promotion and tenure decisions.
See Section V, subsection E of this document.
3. Post Tenure Review: At least once every six years, an evaluation of each tenured faculty member is
conducted by the Department of Statistics. The PTR Committee is responsible for providing the
Department Head the post tenure review of all tenured faculty members. The PTR Committee shall
focus on the faculty member’s performance during the past two years but will also take into account
achievements over a longer period and work in progress. The PTR Committee will recommend to the
Department Head an evaluation of Satisfactory or Unsatisfactory for each faculty member under review
along with supporting documentation of their assessment. If the report from the PTR Committee fi
the faculty member at an Unsatisfactory level in performance, the faculty member will be subject to
Professional Review as specified in the Texas A&M University Post-Tenure Review document,
12.06.99.M0.01.
B. Evaluation Scores
The PTR committee will evaluate the research, teaching, and service performance of every tenured
faculty member at least once every six years. The Department Head will evaluate every faculty member
during the spring semester of every year. The evaluations will be designated as Superior, Satisfactory, or
Unsatisfactory.
For purposes of Post Tenure Review, the Department Head and PTR committee shall rate faculty
members at one of three levels of performance in each of the three categories of research, teaching,
and service, as shown below:
Research
1. Superior
2. Satisfactory
3. Unsatisfactory
Teaching
Superior
Satisfactory
Unsatisfactory
Service
Superior
Satisfactory
Unsatisfactory
The ratings for research, teaching, and service would then be combined to give an overall assessment
of Satisfactory or Unsatisfactory as follows:
Rule 1: If research is unsatisfactory, then the overall rating is unsatisfactory.
Rule 2: If teaching is unsatisfactory, then research must be superior to obtain an overall satisfactory,
otherwise the overall rating is unsatisfactory.
Rule 3: If service is unsatisfactory for one year, then the Department Head will specify corrective
action that must be taken to achieve a satisfactory rating. If service is unsatisfactory for two years
(not necessarily in succession), then the Department Head may, at his or her discretion, provide an
overall rating of un- satisfactory.
The criteria for the determination of the ratings in research, teaching, and service are described in the
next section.
Criteria for Determination of Performance Ratings
1. Research Evaluation: The evaluation of research is mainly based on original scientific research and
the publication of the results of such research. By its very nature, the evaluation of research is
subjective, and the period over which re- search productivity is evaluated also depends on the outcome
of the research. For example, the publication of a research volume may require two or more years, and
213
articles published in leading statistical journals may sometimes have less impact than articles published
in more general scientific outlets. In general, however, the following guidelines are to be used in
evaluating research; the time frame over which these criteria are applied is typically one or two years,
depending on the nature of the work and the publication times of targeted journals.
Superior - Achieve several of the following:
•
•
•
•
•
•
Publications in leading refereed statistics journals or leading refereed journals in allied fi
Receiving significant external peer-reviewed funding for research
Frequent citation of publications
Publication of scholarly book(s)
Selection for a University, College of Science, or professional society outstanding researcher award
Publications and funding resulting from collaborative effort with leading researchers in other
fields
Satisfactory - Achieve several of the following:
•
•
•
•
•
•
Publications in refereed journals
Publication of a chapter in a scholarly book
Presentation of invited and contributed papers at international and national meetings
Publications in refereed proceedings of conferences and professional meetings
Significant self-development activities that lead to increased research and publication effectiveness
Publications and funding resulting from collaborative effort with researchers in other fields
Unsatisfactory
• Not achieving a superior or satisfactory rating
2. Teaching Evaluation: The evaluation of teaching includes classroom instruction; development of
new courses and teaching methods; publication of innovative pedagogical approaches or instructional
materials, including textbooks; and supervision of graduate student research. The following factors
may be used to evaluate the level of teaching performance.
Superior - Achieve several of the following:
•
•
•
•
•
•
•
•
•
•
Selection for a University, College of Science, or professional society outstanding teaching award
Chair of doctoral research committees
Evidence of courses taught at a rigorous and challenging level
Publication of widely adopted or acclaimed instructional material
Outstanding teaching performance as evidenced by outstanding teaching evaluations
Development of innovative pedagogical methods and materials
Development of new courses or major revision of existing courses
Extraordinary service on graduate student advisory committees
Publications in refereed education journals
Evidence of high quality in class preparation, interaction with students, and lectures
Satisfactory - Achieve several of the following:
• Chair of M.S. committees
• Member of graduate student advisory committees
• Evidence of quality in class preparation and interaction with students
214
• Effective coordination of multi-section courses
• Serve as Departmental undergraduate or graduate advisor
• Significant self-development activities leading to enhanced teaching effective- ness
Unsatisfactory
• Continuing or repeated substantial neglect of teaching responsibilities
3. Service Evaluation: The evaluation of service includes service to the students, Department, Texas
A&M University, and service to professional societies, research organizations, governmental agencies,
and the public at large.
Superior - Achieve superior performance in several of the following:
•
•
•
•
•
•
•
•
•
•
•
Officer in a national professional organization
Serving on a major government commission, task force, or board
Administrative leadership role at University, College, or Department level
Editor or member of editorial board of major journal
Member of review panel for national research organization
Program chair at a national meeting
Officer in Faculty Senate
Chair of major Departmental or Texas A&M University committee
Substantial fund raising to support Departmental activities
Member of review panel for national research organization
Obtain positive state, regional, or national recognition for the department
Satisfactory - Achieve excellent performance in several of the following:
Officer in regional or state professional organization
Program or committee chair for regional or state professional meeting
Serving as an active member of the Faculty Senate
Serving on University, College of Science, or Departmental committee
Serving as consultant to business or governmental agencies
Advisor to student organizations
Administrative roles with the Department
Director of the Department’s consulting and internship efforts
Participating in department’s outreach to industry and continuing education activities
Service as a reviewer for major refereed journals
Organizer of a session at a national meeting
Regularly attend Departmental seminars and faculty meetings
Participate in departmental activities, such as, recruitment of new faculty and students, attend
departmental functions outside of the normal business hours, etc.
• Organizing Departmental research workshop
•
•
•
•
•
•
•
•
•
•
•
•
•
Unsatisfactory
•
Continuing or repeated substantial neglect of service responsibilities Behavior that is deemed by the
Department Head and a majority of the Post Tenure Re- view Committee as being detrimental to
the collegial atmosphere and working environment within the Department.
215
VII. Amendment of Bylaws
Amendments to these bylaws may be initiated by either the Department Head or by the petition of
twenty fi e percent of the Departmental faculty. To be adopted, an amendment must be approved by a
two-thirds majority of the Departmental faculty.
VIII. Conflict between Bylaws and Other Regulations
Should any part of these Bylaws be in conflict with regulations of the Texas A&M System, Texas
A&M University, College of Science, State of Texas, or the United States of America, those regulations
take precedence over the Department of Statistics Bylaws.
IX. History of Bylaws
• Accepted By Faculty Vote on March 23, 2015
216
APPENDIX L.
Faculty Biographical Sketches
217
DERYA GÜVEN AKLEMAN
Education:
Middle East Technical Univ.
Middle East Technical Univ.
Texas A&M University
Texas A&M University
Appointments:
Instructor & Assist. Dept. Head
Visiting Assistant Professor
Lecturer
Senior Lecturer
Statistics
Statistics
Statistics
Agricultural Economics
(Marketing & Econometrics)
B.S. (1987)
M.S (1989)
M.S (1993)
Ph.D. (1996)
Dept. of Statistics, Middle East Technical Univ.
Dept. of Statistics, Texas A&M University
Dept. of Statistics, Texas A&M University
Dept. of Statistics, Texas A&M University
June 1996-June 1997
Spring 1998-Fall 2002
Fall 2002-Fall 2008
Fall 2008-present
Teaching:
Last five years:
1. Stat 653: Statistics in Research III, In class and online (three sections, every Spring), Spring2012-present
2. Stat 652: Statistics in Research II, In class and online (three sections, every Fall and Spring), Spring 2006-present
3. Stat 651: Statistics in Research I, In class and online (three sections, every Fall and Spring), Spring 2001-present
4. Stat 642: Methods in Statistics II, online (three sections), Summer 2011
Other TAMU courses thought before:
1. Stat 211: Principles of Statistics I, Fall 2000,01,02,03,04; Spring 2002,03,04,05; Summer 2000,01,02,03
2. Stat 212: Principles of statistics II, Spring 1998,99
3. Stat 302: Statistical Methods, Spring 1998,2000; Fall 1999, 2000; Summer 2000
4. Stat 225: Mechanical Engineering Statistics, Fall 1998,99; Spring 1999
Noteworthy Publications:
1.
Turgut Var, Ozlem Unal, and Derya Güven Akleman, “Tourism in Peripheral Areas: A Case of Three Turkish
Towns”, e-Review of Tourism Research (eRTR) (an international electronic bulletin for tourism research.
http://ertr.tamu.edu), Applied Research Notes, Vol.2, No.2, 2004, 33-37.
2.
Derya Güven Akleman, David A. Bessler and Diana M. Burton, “Modeling Corn Exports and Exchange Rates with
Directed Graphs and Statistical Loss Functions” Clark Glymour and Gregory Cooper, editors: Computation, Causation
and Discovery. Cambridge:MIT Press, 1999, 497-520.
3.
David A. Bessler and Derya Güven Akleman, “Farm Prices, Retail Prices and Directed Graphs: Results for Pork and
Beef” American Journal of Agricultural Economics. Vol. 80, No.5, December 1998, 1144-1149.
4.
Mehmet R. Tolun and Derya Güven, “Analyzing the Inter and Intra Vocabulary Performances in Isolated Speech
Recognition”, Journal of American Voice Input/Output Society, 10, July 1991, 19-37.
University and Department Service:
Last nine years:
1. Member, Department of Statistics Faculty Advisory Committee (April 2014-present)
2. Member, College of Science Diversity Committee, Texas A&M University (Fall 2008-Present)
3. Member, Faculty Senate, Texas A&M University (Fall 2006-Fall 2012, Fall 2014-present)
4. Member, Diversity Committee (now called Workplace, Climate and Diversity) of Faculty Senate, Texas A&M
University (Fall 2007-Fall 2012, Fall 2014-present)
5. Member, College of Science Caucus, Faculty Senate, Texas A&M University (Fall 2006--Fall 2012, Fall 2014present)
1
218
6.
7.
8.
Member, Academic Affairs Committee, Faculty Senate, Texas A&M University (Fall 2006-Fall 2011)
Leader, College of Science Caucus, Texas A&M University (Fall 2007-Fall 2008)
Member, Personal and Welfare Committee, Faculty Senate, Texas A&M University (Fall 2006-Fall 2007)
Membership:
American Statistical Association, 1990-present
Honors (Chosen by students):
The Physicians Centre Hospital Guest Coach, Fall 2008
Grants awarded:
Last five years:
1. Texas A&M University, College of Science, Diversity and Climate Initiatives, $15000, Fall 2013-Fall 2014
2. Texas A&M University, College of Science, Diversity and Climate Initiatives, $15000, Fall 2012-Fall 2013
3. Texas A&M University, College of Science, Diversity and Climate Initiatives, $15000, Fall 2010-Fall 2011
Student committee membership:
Last five years:
Nayab Ali
Elizabeth Goldman
Ashley Schnoor
Nancy Okeudo
Mark Chapman
Jay Clawson
Matthew Austin
Craig Sullivan
Jason Mahaffey
Madhuri Sanagaram
Lisa C. Obrien
Erika Pesek
Lorenzo Gordon
Joel T. Ward
Radhika Sundararaman
Julie Sarzynski
Ashley Hubble
Joshua Wilkerson
Rebekah Zimmermann
Lisa Beatty
Ahlam Mohamad Musa
Karevaradharaj Doraiswamy Selvaraj
Eduardo Drucker
Stephen Dauphin
Susan Powell
Chanin L. Monestero
Mark McKinnon
Kathryn Lemons
Suzanne Fluke
Jason Daniel Tepe
Janessa Kathleen Tucker
Meghan Waterbury
Gail Faith Thorne
David Lee Fleeger
Sarah Evangeline
Zachary Dean Adian
Scott Harold Copperman
Janell Christine (Eck) Martin
MS in STAT
MS in Math
MS in Math
MS in Math
MS in Math
MS in Math
MS in Math
MS in Math
MS in Math
MS in INEN
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in INEN
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in Math
Ph.D in EDUCATION
MS in INEN
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
(Graduated Spring 2014)
(Graduated Spring 2014)
(Graduated Spring 2014)
(Graduated Summer 2014)
(Graduated Spring 2014)
(Graduated Spring 2013)
(Graduated Fall 2012)
(Graduated Fall 2013)
(Graduated Spring 2013)
(Graduated Fall 2012)
(Graduated Fall 2012)
(Graduates Spring 2014)
(Graduated Summer 2012)
(Graduated Spring 2013)
(Graduated Spring 2012)
(Graduated Fall 2012)
(Graduated Spring 2013)
(Graduated Summer 2013)
(Graduated Spring 2013)
(Graduated Spring 2013)
2
219
Bradley Keith Scott
Stephanie Gail Nite
Janessa Kathleen Tucker
Teo J. Paoletti
Michael Vieira Serpa
Michael Kenneth Soper
Jennifer Kristi Ulrich
Scott Harold Copperman
Janell Christine Eck
Bradley Keith Scott
Camellia Blackbery
Ebru Celile Ozbay
Christopher M. Golubski
Rodney Dale Wyrick
Thomas Andrew Moseder
Rudy C. Medina
Cynthia Lucille Bervig
Betsy McIver G Jones
Daniel J. Groom
Joshua Dustin D. Hammond
Scott T. Dickie
Kurt Michael Bruggeman
Damon McDaniel
Richard Uber
Alexander Munson
Sarah Martin Luther
Diana Wright Branton
Yanjing Liu
April Lile Carne
Ryan Albert Melbard
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
(Graduated Fall 2011)
(Graduated Summer 2012)
(Graduated Fall 2010)
(Graduated Fall 2011)
(Graduated Spring 2011)
(Graduated Spring 2011)
(Graduated Spring 2013)
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
(Graduated Spring 2011)
(Graduated Fall 2010)
(Graduated Summer 2010)
(Graduated Spring 2011)
(Graduated Spring 2011)
MS in MATH
(Graduated Fall 2010)
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
MS in MATH
(Graduated Summer 2010)
(Graduated Spring 2010)
(Graduated Fall 2010)
(Graduated Summer 2010)
(Graduated, Summer 2009)
(Graduated, Fall 2009)
(Graduated, Summer 2009)
(Graduated, Summer 2009)
(Graduated, Fall 2009)
(Graduated, Spring 2009)
3
220
ANIRBAN BHATTACHARYA
Education:
Indian Statistical Institute, Kolkata, India
Indian Statistical Institute, Kolkata, India
Duke University
Appointments:
Assistant Professor
Postdoctoral Associate
Statistics
Statistics
Statistics
Texas A&M Univeristy
Duke University
B.S. (2006)
M.S. (2008)
Ph.D. (2012)
2013 – Pres.
2012–2013
Publications:
i. Last five years:
1. (with Dunson, D.B.) Sparse Bayesian infinite factor models. Biometrika, (2011), 98(2), 291-306.
2. (with Dzirasa, K., Mcgrarity, D., and others) Impaired limbic gamma oscillatory synchrony during anxiety
related behavior in a genetic mouse model of bipolar mania. Journal of NeuroScience, (2011), 31(17), 64496456.
3. (with Dunson, D.B.) Simplex factor models for multivariate unordered categorical data. Journal of the American Statistical Association, (2012), 107, 362-377.
4. (with Pati, D., Dunson, D.B.) Anisotropic function estimation using multi-bandwidth Gaussian processes. The
Annals of Statistics, (2014), 42(1), 352-381.
5. (with Pati, D., Pillai, N.S. and Dunson, D.B.) Posterior contraction in sparse Bayesian factor models for
massive covariance matrices. The Annals of Statistics, (2014), 42(3), 1102-1130.
6. (with Pati, D., Pillai, N.S. and Dunson, D.B.) Dirichlet-Laplace priors for optimal shrinkage, Journal of the
American Statistical Association, In press.
7. (with Zhou, J., Herring, A.H. and Dunson, D.B.) Bayesian factorizations of big sparse tensors. Journal of the
American Statistical Association, In press.
8. (with Pati, D. and Cheng, G.) Optimal Bayesian estimation in random covariate design with a rescaled Gaussian process prior. Journal of Machine Learning Research, To appear.
Grants:
1. PI, Office of Naval Research (ONR BAA 14-0001), $105,721, Bayesian inference for high-dimensional covariance
matrices and tensors, 2014-2016.
Awards and Honors:
1. Leonard J. Savage Dissertation Award (Theory and Methods) 2012, awarded by the International Society for
Bayesian Analysis (ISBA)
2. Student paper award from Section of Bayesian Statistical Science (SBSS), 2011
3. Member of Editorial Boards:
Statistics and Probability Letters (2015-Present).
1
221
Service:
1. Session chair, Joint Statistical Meetings, Montreal, Canada, 2013
2. Organized session on “Emerging trends in Bayesian nonparametrics”, International Symposium on Business and
Industrial Statistics / Conference of the ASA Section on Statistical Learning and Data Mining (ISBIS/SLDM),
Durham, NC, 2014.
3. Session chair, International Society of Bayesian Analysis (ISBA) World Meetings, Cancun, Mexico, 2014.
4. Colloquium chair, Department of Statistics, Texas A&M University, 2014 - Pres.
5. Reviewer for Annals of Applied Statistics, Annals of Statistics, Bayesian Analysis, Bernoulli, Biometrika, Electronic
Journal of Statistics, Journal of the American Statistical Association, Journal of Machine Learning Research among
others.
6. Member of PhD qualifying exams committee, Department of Statistics, Texas A&M University, 2014 - Pres.
2
222
JULIE HAGEN CARROLL
Education:
Texas A&M University
Texas A&M University
Texas A&M University
Mathematics
Industrial Engineering
Statistics
B.S. (1979)
M.S (1985)
M.S. (1990)
Appointments:
Lecturer
Senior Lecturer
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
1992-1999
1999-Pres.
Course Taught:
STAT 303
200+ undergraduates both Fall and Spring
1992-Pres.
Service:
Undergraduate Service Committee
Assistantship Duties Committee
Corps of Cadet Academic Advisor for Company F-2
Awards:
TAMU Fish Camp Namesake
TAMU Association of Former Students College Level Teaching Award
223
RAYMOND J. CARROLL
Education:
University of Texas at Austin
Purdue University
Mathematics
Statistics
Appointments:
Distinguished Professor and Harlin Chair
Professor and Fairhill Chair
Assistant, Associate and Full Professor
B.S. (1971)
Ph.D. (1974)
Department of Statistics, TAMU
Department of Epidemiology
University of North Carolina
1987–1998 and 2000-present
University of Pennsylvania, 1998-2000
1974-1987
Publications:
i. Last five years, selected from 87 papers, 2010-present
1. Martinez, J. G., Huang, J. Z., Burghardt, R. C., Barhoumi, R. and Carroll, R. J. (2010). Use of multiple singular
value decompositions to analyze complex intracellular calcium ion signals. Annals of Applied Statistics, 3,
1467-1492.
2. Sinha, S., Mallick, B. K., Kipnis, V. and Carroll, R. J. (2010). Semiparametric Bayesian analysis of nutritional
epidemiology data in the presence of measurement error. Biometrics, 66, 444-454.
3. Zhou, L., Huang, J., Martinez, J. G., Maity, A., Baladandayuthapani, V. and Carroll, R. J. (2010). Reduced
rank mixed effects models for spatially correlated hierarchical functional data. Journal of the American Statistical Association, 105, 390-400.
4. Staicu, A.-M., Crainiceanu, C. M. and Carroll, R. J. (2010). Fast methods for spatially correlated multilevel
functional data. Biostatistics, 11, 177-194.
5. Li, Y., Wang, N. and Carroll, R. J. (2010). Generalized functional linear models with semiparametric singleindex interactions. Journal of the American Statistical Association, 105, 621-633.
6. Carroll, R. J., Hart, J. D. and Ma, Y. (2011). Local and omnibus tests in classical measurement error models.
Journal of the Royal Statistical Society, Series B, 73, 81-98.
7. Carroll, R. J., Delaigle, A. and Hall, P. (2011). Testing and estimating shape-constrained nonparametric
density and regression in the presence of measurement error. Journal of the American Statistical Association,
106, 191-202.
8. Zhang, S., Midthune, D., Guenther, P. M., Krebs-Smith, S. M., Kipnis, V., Dodd, K. W., Buckman, D. W.,
Tooze, J. A., Freedman, L. S. and Carroll, R. J. (2011). A new multivariate measurement error model with
zero-inflated dietary data, and its application to dietary assessment. Annals of Applied Statistics, 5, 1456-1487.
9. Wang, L., Liu, X., Liang, H. and Carroll, R. J. (2011). Generalized additive partial linear models— polynomial
spline smoothing estimation and variable selection procedures. Annals of Statistics, 39, 18271851.
10. Ma, Y., Hart, J. D. and Carroll, R. J. (2011). Density estimation in several populations with uncertain population membership. Journal of the American Statistical Association, 106, 1180-1192.
11. Yi, G. Y. Y., Ma, Y and Carroll, R. J. (2012). A robust, functional generalized method of moments approach
for longitudinal studies with missing responses and covariate measurement error. Biometrika, 99, 151-165.
12. Wei, Y., Ma, Y. and Carroll, R. J. (2012). Multiple imputation in quantile regression. Biometrika, 99, 423-438.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4059083/
13. Carroll, R. J., Midthune, D., Subar, A. F., Shumakovich, M., Freedman, L. S., Thompson, F. E. and Kipnis, V.
(2012). Taking advantage of the strengths of two different dietary assessment instruments to improve intake
estimates for nutritional epidemiology. American Journal of Epidemiology, 175, 340-347.
14. Kipnis, V., Midthune, D., Freedman, L. S. and Carroll, R. J. (2012). Regression calibration with more instruments than mismeasured variables. Statistics in Medicine, 31, 2713-2732.
1
224
15. Carroll, R. J., Delaigle, A. and Hall, P. (2012). Deconvolution when classifying noisy data involving transformations. Journal of the American Statistical Association, 106, 1166-1177.
16. Chen, Y.-H., Chatterjee, N. and Carroll, R. J. (2013). Using shared genetic controls in studies of geneenvironment interactions. Biometrika, 100, 319-338.
17. Xun, X., Cao, J., Mallick, B. K., Maity, A. and Carroll, R. J. (2013). Parameter estimation of partial differential
equation models. Journal of the American Statistical Association, 108, 1009-1020.
18. Carroll, R. J., Delaigle, A. and Hall, P. (2013). Unexpected properties of bandwidth choice when smoothing
discrete data for constructing a functional data classifier. Annals of Statistics, 41, 27392767.
19. Li, Y., Wang, N. and Carroll, R. J. (2013). Selecting the number of principal components in functional data.
Journal of the American Statistical Association, 108, 1284-1294.
20. Serban, N., Staicu, A.-M. and Carroll, R. J. (2014). Multilevel cross-dependent binary longitudinal data.
Biometrics, 69, 903-913.
21. Guenther, P. M., Kirkpatrick, S. L., Reedy, J., Krebs-Smith, S. M., Buckman, D. W., Dodd, K. W. Casavale,
K. O. and Carroll, R. J. (2014). Healthy Eating Index-2010 is a valid and reliable measure of diet quality
according to the 2010 Dietary Guidelines for Americans. Journal of Nutrition, to appear.
22. Sarkar, A., Mallick, B. K., Staudenmayer, J., Pati, D. and Carroll, R. J. (2014). Bayesian semiparametric
density deconvolution in the presence of conditionally heteroscedastic measurement errors. Journal of Computational and Graphical Statistics, 25, 1101-1125.
23. Lian, H., Liang, H. and Carroll, R. J. (2014). Variance function partially linear single-index models. Journal
of the Royal Statistical Society, Series B, 77, 171-194.
24. Ma, Y. and Carroll, R. J. (2015). Semiparametric estimation in the secondary analysis of case-control studies.
Journal of the Royal Statistical Society, Series B, to appear.
25. Yi, G. Y., Ma, Y., Spiegelman, D. and Carroll, R. J. (2015). Functional and structural methods with mixed
measurement error and misclassification in covariates. Journal of the American Statistical Association, to
appear.
ii. Other Noteworthy Publications:
1. Ruppert, D., Wand, M. P. and Carroll, R. J. (2003). Semiparametric Regression. Cambridge University Press.
2. Carroll, R. J., Ruppert, D., Stefanski, L. A. and Crainiceanu, C. M. (2006). Measurement Error in Nonlinear
Models: A Modern Perspective, Second Edition. Chapman and Hall CRC Press.
3. Liang, F., Liu, C. and Carroll, R. J. (2010). Advanced Markov Chain Monte Carlo: Learning from Past
Samples. Wiley, New York. ISBN: 978-0-470-74826-8.
Grants in last five years:
1. National Cancer Institute (CA-57030), support for basic research, Measurement Error, Nutrition and Breast-Colon
Cancer, 1992-present (P.I.). Funded 2005-2015 via a MERIT Award. Renewed May 1, 2015.
2. National Cancer Institute (CA-90301), support for a training program in Biostatistics, Bioinformatics and the Biology of Nutrition and Cancer, 2001-present (P.I.). Funded through 2016.
3. King Abdullah University of Science and Technology (KAUST, P.I.): support for the funding of the Texas A&M
University Institute of Applied Mathematics and Computational Science, 2008-2014.
4. National Science Foundation, co-investigator on Bayesian Data Mining Approaches for Biological Threat Detection
(B. Mallick, P.I.), 2009-2012.
Awards and Honors (Selected):
1. Gottfried E. Noether Senior Scholar Award and Lecture, American Statistical Association, 2014
2. Elected Fellow, American Association for the Advancement of Science, 2014.
2
225
3. Honorary doctorate, Institut de Statistique, Universit Catholique de Louvain, 2012.
4. Mitchell Prize for Bayesian Statistics, 2003 (from the International Society for Bayesian Analysis).
5. Fisher Award and Lecture, 2002 (from COPSS)
6. Outstanding Achievement Award for Promoting Diversity, Texas A&M University, 1996.
7. Wilcoxon Prize, American Society for Quality Control, 1986.
8. COPSS Presidents’ Award (IMS, ASA, ENAR, WNAR, CSS), 1988.
9. 13 named lectures at universities
Service (Selected):
1. Editor, Biometrics (1997-2001).
2. Editor, Journal of the American Statistical Association, Theory and Methods Section (1988-1990).
3. Founding Chair, NIH Study section on Biostatistics (BMRD), 2002-2004.
Students Supervised (From 43):
1. Leonard A. Stefanski (1983). Estimation for binary regression models. Professor, North Carolina State University
(past editor of the Journal of the American Statistical Association).
2. Douglas Simpson (1985). Robust estimation for discrete data. Professor, University of Illinois (also department
head).
3. Marie Davidian (December, 1986). Variance function estimation in regression. Professor, North Carolina State
University (also past editor, Biometrics, past President of the American Statistical Association).
4. C. Y. Wang (August, 1993). Analysis of case-control studies. Full Member, Fred Hutchinson Cancer Research
Center.
5. J. S. Morris (July, 2000). Statistical models for colon cancer cell mechanisms. Professor, M. D. Anderson Cancer
Research Center.
6. Hua Liang (March, 2001). Semiparametric statistical methods and computation. Professor, George Washington
University.
7. Tanya Apanasovich (June, 2004). Longitudinal and spatial methods in the analysis of Aberrant Crypt Foci in colon
carcinogenesis. Associate Professor, George Washington University.
8. Veerabhadran Baladandayuthapani (June, 2005). Bayesian methods in Bioinformatics. Associate Professor, University of Texas M. D. Anderson Cancer Center.
9. Yehua Li (June, 2006). Functional data analysis in biology. Associate Professor, Iowa State University.
10. Bo Li (August, 2006). Spatial statistics. Associate Professor, University of Illinois.
11. Arnab Maity (August, 2008). Semiparametric methods for repeated measures data. Assistant Professor, North
Carolina State University.
12. Abhra Sarkar (May 2014). Bayesian analysis of high dimensional data. Postdoctoral fellow, Duke University.
Post-Docs Supervised (From 19):
1. Helmut K¨uchenhoff, Professor, University of Munich
2. Danh V. Nguyen, Professor, University of California at Irvine
3. Ana-Maria Staicu, Assistant Professor, North Carolina State University
4. Anindya Bhadra, Assistant Professor, Purdue University
5. Tanya Garcia, Assistant Professor, Texas A&M School of Public Health
3
226
WILLA W CHEN
Education:
New York University
New York University
Appointments:
Professor
Associate Professor
Assistant Professor
Postdoc
Statistics
Statistics
Ph.D (2000)
MS (1995)
Department of Statistics, Texas A&M University
Department of Statistics,Texas A& M University
Department of Statistics,Texas A& M University
Watson Research Center, IBM
2012 – Present
2007-2012
2001-2007
2000-2001
Publications:
i. Last five years:
1. Chen W., Deo, R. and Yi, Y. (2013). Uniform Inference in Predictive Regression Models, Journal of Business
& Economic Statistics 31, 525-533
2. Chen W. and Deo R. (2012). The Restricted Likelihood Ratio Test for Autoregressive Processes, Journal of
Time Series Analysis 33, 325-339
3. Chen, W. (2010). Efficiency in Estimation of Memory, Journal of Statistical Planning and Inference 140,
3820-3840
4. Chen, W. and Deo, R. (2010). Weighted Least Squares Approximate Restricted Likelihood Estimation for
Vector Autoregressive Processes, Biometrika 97, 231-237
5. Chen, W. and Deo, R. (2009). The Restricted Likelihood Ratio Test at the Boundary in Autoregressive Series,
Journal of Time Series Analysis 30, 618-630
6. Chen, W. and Deo, R. (2009). Bias Reduction and Likelihood Based Almost-Exactly Sized Hypothesis Testing
in Predictive Regressions using the Restricted Likelihood, Econometric Theory 25, 1143-1179
ii. Other Noteworthy Publications:
1. Chen, W., and Hurvich, C. (2008). Fractional Cointegration, Chapter in the Handbook of Financial Time
Series, Springer
2. Chen, W., and Hurvich, C. (2006). Semiparametric Estimation of Fractional Cointegrating Subspaces, Annals
of Statistics 27, 2939-2979
3. Chen, W. and Deo, R. (2006). Estimation of Mis-specified Long Memory Models,” Journal of Econometrics
134, 257–281
4. Chen, W., Hurvich, C. and Lu, Y. (2006). On the Correlation Matrix of the Discrete Fourier Transform and the
Fast Solution of Large Toeplitz Systems For Long-Memory Time Series, Journal of the American Statistical
Association 101, 812-821
5. Chen, W. and Deo, R. (2006). The Variance Ratio Statistic at Large Horizons, Econometric Theory 22,
206–234
6. Chen, W. and Deo, R. (2004). Power Transformations to Induce Normality and Their Applications, Journal
of the Royal Statistical Society, Series B 66, 117–130
7. Chen, W. and Deo R. (2004). A Generalized Portmanteau Goodness-of-Fit Test for Time Series Models,
Econometric Theory 20, 382–416
1
227
8. Chen, W. and Hurvich, C. (2003). Estimating Fractional Cointegration in the Presence of Polynomial Trends,
Journal of Econometrics 117, 95–121
9. Chen, W. and Hurvich, C. (2003). Semiparametric Estimation of Multivariate Fractional Cointegration, Journal of the American Statistical Association 98, 629–642
10. Hurvich, C. and Chen W. (2000). An Efficient Taper for Potentially Overdifferenced Long-Memory Time
Series, Journal of Time Series Analysis 21, 155–180
11. Deo R. and Chen W. (2000). On the Integral of the Squared Periodogram, Stochastic Processes and Their
Applications 85, 159–176
Grants in last five years:
i. Last five years:
1. National Science Foundation, $143,047, ”Restriction likelihood in time series: Applications to moderate and
near integrated autoregressions, conintegration, panel data and nonlinear time seires”, 2010-2014.
ii. Other Noteworthy Grants:
1. National Science Foundation, $116,292, ”Long Memory Time Series Modelling: Computational and Statistical Efficiency, Nonstationarity/Noninvertibility and Goodness of Fit”, 2006-2010.
2. National Science Foundation, $107,483, ”Fractional Cointegration, Data Tapering and Estimation of Misspecified Models in Long Memory Time Series”, 2003-2006.
Editorial Work:
Member of Editorial Boards:
Journal of the American Statistical Association – T&M (2014-Present).
Journal of Computational and Graphical Statistics (2009-Present).
Electronic Journal of Statistics (2010-2013).
Journal of the American Statistical Association – A&CS (2009-2012).
Students Supervised:
Priya Kohli (2012), Ph.D (Co-advised with M. Pourahmadi)
Dissertation: Prediction of Stationary Random Fields.
2
228
DAREN B.H. CLINE
Education:
Colorado State University
Colorado State University
Harvey Mudd College
Statistics
Statistics
Mathematics
Appointments:
Professor
Assoc. Professor
Asst. Professor
Visiting Research Asst. Prof.
Visiting Assistant Prof.
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Center for Stochastic Processes, Univ. of North Carolina
Department of Statistics, University of British Columbia
Ph.D. (1983)
M.S. (1980)
B.S. (1978)
2002–2015
1990–2002
1984–1990
1986
1983–1984
Publications:
i. Last Five Years:
1. (2015) Z. Yao, D.B.H. Cline and D. Loguinov, Unstructured P2P link lifetimes redux, to appear IEEE Trans. on
Networking.
2. (2015) A. Banaei, D.B.H. Cline, C. Geoghiades and S. Cai, On asymptotic statistics for geometric routing
schemes in wireless ad-hoc networks, to appear IEEE Trans. on Networking.
3. (2015) R. Kumar, D.B.H. Cline and P. Gardoni, A stochastic framework to model deterioration in engineering
systems, Structural Safety to appear.
4. (2014) Z. Yao, D.B.H. Cline, X. Wang, and D. Loguinov, Unifying models of churn and resilience for
unstructured P2P graphs, IEEE Trans. on Parallel and Distributed Systems 25, 2475–2485.
5. (2011) D.B.H. Cline, Irreducibility and continuity assumptions for positive operators with application to threshold
GARCH models, Adv. Appl. Probab. 43, 49–76.
6. (2010) Z. Yao, D.B.H. Cline, and D. Loguinov, In-degree dynamics of large-scale P2P systems, ACM
SIGMETRICS Performance Evaluation Review 38, 37–42.
ii. Other Noteworthy Publications:
1. (2009) D.B.H. Cline, Thoughts on the connections between threshold time series models and dynamical systems.
Exploration of a Nonlinear World: An Appreciation of Howell Tong's Contributions to Statistics, K.-S. Chan, ed.,
World Scientific, 165–181.
2. (2007) D.B.H. Cline, Stability of nonlinear stochastic recursions with application to nonlinear AR-GARCH
models, Adv. Appl. Probab. 39, 462–491.
3. (2004) D.B.H. Cline and H.H. Pu, Stability and the Lyapounov exponent of threshold AR-ARCH models, Ann.
Appl. Probab. 14, 1920–1949.
4. (1994) D.B.H. Cline, Intermediate regular and Π-variation, Proc. London Math. Soc. 68, 594–616.
5. (1988) R.J. Carroll and D.B.H. Cline, An asymptotic theory for weighted least squares with weights estimated by
replication, Biometrika 75, 35–43.
Research Grants:
i. Last Five Years:
1. National Science Foundation (Co-PI, with Dmitri Loguinov), total award $473,420 (my share $95,228), CSR:
Small: Yesterday’s News: Theory of Staleness under Data Churn, 2013–2016.
ii. Other Noteworthy Grants:
1. National Science Foundation (PI), Regular Variation: Analytic Approaches to Probability and Statistics, 1991–
1993.
2. National Science Foundation (Co-PI, with Tailen Hsing), Applications of Asymptotic Structures for Dependence,
Distribution Tails and Characteristic Functions, 1990.
Awards and Honors:
1. James L. Madison Award, Statistics, Colorado State University.
2. The Association of Former Students Distinguished Teaching Award, College of Science, Texas A&M University.
1
229
Selected National, University and Department Service:
1. Promotion and Tenure Committee, Department of Statistics (various).
2. Graduate Curriculum Committee, Department of Statistics (various).
3. Workshop on Predictive Modeling, National Science Foundation (2007).
4. Faculty Advisor Council, College of Science (2002–2008).
5. Faculty Grievance Committee, College of Science (2001–2004).
6. Faculty Senate, Texas A&M University (1992–1994).
Students Supervised:
i. Ph.D.:
1. (2014) Bo Wei (Co-chair with Sila Çetinkaya, Industrial and Systems Engineering), Stochastic Clearing Models
with Applications in Shipment Consolidation.
2. (2003) Thomas R. Boucher, V-Uniform Ergodicity of Threshold Autoregressive Nonlinear Time Series.
3. (1995) Huay-min H. Pu, Recurrence and Transience for Autoregressive Nonlinear Time Series.
ii. Most Recent M.S.:
1. (2013) Steven Jackson
2. (2012) Kaitlin Olmstead
3. (2008) Jie Li
4. (2006) Jessica Wickersham
5. (2004) Lian Liu
6. (2004) Bo Li
2
230
ALAN DABNEY
Education:
University of Texas at Arlington
University of Washington
University of Washington
Appointments:
Associate Professor
Assistant Professor
Mathematics B.S. (1999)
Biostatistics M.S. (2001)
Biostatistics Ph.D. (2006)
Department of Statistics, Texas A&M University
Department of Statistics, Texas A& M University
2011-Pres.
2006-2011
Publications:
i. Last five years:
1. Ball, R.L., Feiveson, A.H., Schlegel, T.T., Starc, V., and Dabney, A.R. Predicting “heart age” using
electrocardiography, Journal of Personalized Medicine, (2014), 4, 65-78.
2. Turner, S., and Dabney, A.R. A story-based simulation for teaching sampling distributions, Teaching Statistics,
(2014), 37, 23-25.
3. Menon, R., Watson, S., Thomas, L., Allred, C., Dabney, A.R., Azcarate-Peril, M., and Sturino, J. Diet complexity
and estrogen receptor β–status affect the composition of the murine intestinal microbiota, Applied and
Environmental Microbiology, (2013), 79, 5763-5773.
4. Karpievitch, Y.V., Dabney, A.R., and Smith, R.D. Normalization and missing value imputation for label-free LCMS analysis, BMC Bioinformatics, (2012), 13, S5.
5. Taverner, T., Karpievitch, Y.V., Polpitiya, A., Brown, J., Dabney, A.R., Anderson, G.A., and Smith, R.D. DanteR:
An extensible R-based tool for quantitative analysis of –omics data, Bioinformatics, (2012), 28, 2404-2406.
6. Tekwe, C.D., Carroll, R.J., and Dabney, A.R. Application of survival analysis methodology to the quantitative
analysis of LC-MS proteomics data, Bioinformatics, (2012), 28, 1998-2003.
7. Wang, X., Anderson, G.A., Smith, R.D., and Dabney, A.R. A hybrid approach to protein differential expression in
mass spectrometry-based proteomics, Bioinformatics, (2012), 28, 1586-1591.
8. Stanley, J., Adkins, J.N., Slysz, G., Monroe, M., Purvine, S., Karpievitch, Y.V., Anderson, G.A., Smith, R.D., and
Dabney, A.R. A statistical method for assessing peptide identification confidence in accurate mass and time tag
proteomics, Analytical Chemistry, (2011), 83, 6135-6140.
9. Karpievitch, Y.V., Polpitiya, A., Adkins, J.N., Anderson, G.A., Smith, R.D., and Dabney, A.R. Mass
spectrometry-based proteomics: Biological and technological aspects, Annals of Applied Statistics, (2010), 4,
1797-1823.
ii. Other Noteworthy Publications:
1. Klein, G., and Dabney, A.R. The Cartoon Introduction to Statistics, Farrar, Straus, and Giroux, (2013).
Grants in last five years:
i. Last five years:
1. National Institutes of Health, $1,805,862, “Epigenetics of the Aging Astrocyte: Implications for Stroke”, 20112016, Role: Co-I.
2. American Cancer Society, $718,000, “Effects of Estrogen on Sporadic and Inflammation-Associated Colon
Cancer”, 2011-2015, Role: Co-I.
3. U.S. Department of Agriculture, $9,750,000, “Integrated Program for Reducing Bovine Respiratory Disease
Complex in Beef and Dairy Cattle”, 2011-2016, Role: Co-I.
4. National Science Foundation, $997,710, “UBM-Institutional: Integrated Undergraduate Research Experiences in
Biological and Mathematical Sciences”, 2010-2015, Role: Co-I.
ii. Other Noteworthy Grants:
1. Subcontract from Pacific Northwest National Laboratory, $350,000, “Statistical Methods for LC-MS Proteomics”,
2007-2009, Role: PI.
1
231
Awards and Honors:
1. TAMU Distinguished Achievement College-Level Award in Teaching from the Association of Former Students
(2011).
2. TAMU College of Science Montague-Center for Teaching Excellence Scholar (2009).
Service:
1. 2014 Member, Undergraduate Program Committee, TAMU Department of Statistics.
2. 2012-2014 Member, M.S. Qualifying Exam Committee, TAMU Department of Statistics.
3. 2012 Member, Selection Committee, The Association of Former Students’ College-Level Teaching Awards.
4. 2012 Member, External Advisory Board, TAMU AgriLife Genomics and Bioinformatics Services (TAGS) Core.
5. 2011-2014 Member, TAMU Undergraduate Academic Appeals Panel.
Students Supervised:
Ph.D. Students:
Robyn Ball (2013), Ph.D., Texas A&M University
Dissertation: Statistical Methods for High-Dimensional Biological Data.
Xuan Wang (2011), Ph.D., Texas A&M University
Dissertation: Statistical Methods for the Analysis of Proteomics Data.
Post-Docs:
Carmen Tekwe, Texas A&M University, 2011-2013.
Yuliya Karpievitch, Texas A&M University, 2007-2010.
M.S. Students:
More than 15 M.S. students supervised, including many students in the Distance Learning program.
2
232
PAUL FREDERICK DAHM
Education:
Iowa State University
Iowa State University
Iowa State University
Distributed Studies (minors in Mathematics, Statistics & Physics) B.S. (1973)
Statistics M.S. (1977)
Statistics Ph.D. (1979)
Appointments:
Professor
Graduate Advisor
Associate Professor
IPA/Visiting Statistician
Assistant Professor
Department of Statistics, Texas A& M University
Department of Statistics, Texas A& M University
Department of Statistics, Texas A& M University
Biostatistics Branch, National Cancer Institute
Department of Statistics, Texas A& M University
1993-present
1989-2014
1985-1993
1988-1989
1979-1985
Publications:
i. Last five years: None
ii. Manuscripts in revision or preparation:
1. Abdulsalam, F., Pittroff, W. and Dahm, P.F. Quantitative Simulation Model Evaluation. In revision.
2. Lu, M. and Dahm, P.F. Evaluation of trace-driven stochastic simulation models. (Working title) In preparation.
3. Lu, M. and Dahm, P.F. Tests for independence in the evaluation of stochastic simulation models. In preparation.
Grants in last five years:
i. Last five years: None
ii. Other Noteworthy Grants:
1. National Institute of Mental Health, “Partial Hospitalization of High Risk Suicidal Youth,” 1991-1993.
(Collaborator)
2. National Institutes of Health, “NIH: Chromosomal Rearrangement Incorporation in Mammals,” 1993-1996. (Co
Principal Investigator with I. M. Greenbaum)
3. United States Department of Agriculture, “Estimation of Growth Curves with U. S. Sheep Experiment Station
Researchers,” 1998-1999. (Statistical Consultant)
4. Food and Agricultural Organization of the United Nations, $10,000, “Statistical Design and Analytical Support for
the Afghanistan Livestock Census,” 2002-2005. (Statistical Consultant)
5. National Institutes of Health, $250,000, “Sex Steroids and TMJ Pain,” 2005-2009. (Collaborator)
Awards and Honors:
1. Texas A&M Association of Former Students College of Science Teaching Award (1992)
2. Texas A&M University International Excellence Award (2000)
3. Texas A&M Association of Former Students Distinguished Achievement Award in Student Relations (2001)
Service:
Sessions Organized and Work at National and International Meetings:
1. Program Chair of General Methodology Sections of the Joint Statistical Meetings, Orlando, FL, 1987.
Students Supervised: (Listings are for Ph.D. Committees Chaired or Co-chaired only)
Yoshihiko Tsukuda (1985) (Chair)
Dissertation: Asymptotic Expansions of the Distributions of Certain Test Statistics for the Slope in a Linear Functional
Relationship.
Ed Miller (1987) (Co-chair)
Dissertation: Inference for the Parameters of the Complete Symmetry Covariance Structure Model.
Jong-Duk Kim (1989) (Chair)
Dissertation: Construction of Restricted D-Optimal Designs for Polynomial Regression Models.
1
233
Kyung Chang (1990) (Chair)
Dissertation: Asymptotic Expansions of the Distributions of Studentized Test Statistics for the Slope Parameter in Simple Linear
Structural Relationships.
Mahinda Karunaratne (1991) (Chair)
Dissertation: Estimating the Odds Ratio under Double Sampling.
Anne Coleman (1995)
Dissertation: Variance Components Estimation with Missing Cells.
Fayez Abdul-Salam (1995) (Chair)
Dissertation: Small Sample Inference for the Structural and Functional Simple Linear Measurement Error Models.
Tony White (1998) (Chair)
Dissertation: A PC Program for the Parameter Estimation of Nonlinear Growth Models with Unequally Spaced Correlated
Observations.
Ann Olmsted (1999) (Chair)
Dissertation: Algorithms Using Chi-squared and Other Goodness of Fit Tests to Identify a High-expectation Subset of
Independent Poisson Random Variables, or a Subset of Multinomial Cells Having Relatively High Probabilities, with
Applications in Chromosomal Fragile Site Identification.
Dan Gaile (2003) (Chair)
Dissertation: Development of Statistical Tools with Applications in Radiation Hybrid and Linkage Mapping.
Chris Hintze (2005) (Chair)
Dissertation: Modeling Correlation in Binary Count Data with Application to Fragile Site Identification.
Ming Lu (2014) (Chair)
Dissertation: Investigation of Simple Linear Measurement Error Models (SLMEMs) with Correlated Data.
Rupa Kanchi (2014) (Co-chair)
Dissertation: Recombination Studies and Development of QTL-targeted Tiled Introgression Libraries by Marker Assisted
Backcrossing Across Four Maize Chromosomal Segments.
2
234
JEFFREY D. HART
Education:
B.S., Mathematics, Southern Methodist University (1977)
M.S., Statistics, Southern Methodist University (1979)
Ph.D., Statistics, Southern Methodist University (1981)
Appointments:
Adjunct Professor
Visiting Professor
Professor
Research Fellow
Visiting Adjunct Associate Professor
Visiting Associate Professor
Associate Professor
Assistant Professor
Assistant Professor
Department of Biostatistics, M.D. Anderson Cancer Center
Department of Statistics, Limburgs Universitair Centrum
Department of Statistics, Texas A&M University
Statistics Research Section, Australian National University
Department of Statistics, North Carolina State University
Institut f¨ur Wirtschaftstheorie II, Universit¨at Bonn
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Mathematics, University of Arkansas
20071997-98
19941989
1989
1988
1988-94
1982-88
1981-82
Publications:
i. Last five years:
1. Hart, J.D. (2009). Frequentist-Bayes lack-of-fit tests based on Laplace approximations. Journal of Statistical
Theory and Practice 3 681-704.
2. Claeskens, G. and Hart, J.D. (2009). Goodness-of-fit tests in mixed models (with discussion). TEST 18
213-239.
3. Hart, J.D. (2009). Discussion of “Parametric Versus Nonparametrics: Two Alternative Methodologies,” by
E.L. Lehmann. Journal of Nonparametric Statistics 21 411-413.
4. Park, B.-J. , Lord, D. and Hart, J.D. (2010). Bias properties of Bayesian statistics in finite mixture of negative
binomial regression models in crash data analysis. Accident Analysis and Prevention 42 741-749.
5. Savchuk, O.Y., Hart, J.D. and Sheather, S.J. (2010). Indirect cross-validation for density estimation. Journal
of the American Statistical Association 105 415-423.
6. Savchuk, O.Y., Hart, J.D. and Sheather, S.J. (2010). An empirical study of indirect cross-validation. Nonparametric Statistics and Mixture Models – A Festschrift in Honor of Thomas P Hettmansperger (D.R. Hunter,
D.S.P. Richards and J.L. Rosenberger, eds.), World Scientific 288-308.
7. Song, J. and Hart, J.D. (2010). Bootstrapping in a high-dimensional but very low sample size problem. Journal
of Statistical Computation and Simulation 80 825-840.
8. Ma, Y., Hart, J.D., Janicki, R. and Carroll, R.J. (2011). Local and omnibus goodness-of-fit tests in classical
measurement error models. Journal of the Royal Statistical Society, Series B 73 81-98.
9. Kim, J. and Hart, J.D. (2011). A change-point estimator using local Fourier series. Journal of Nonparametric
Statistics 23 83-98.
10. Hart, J.D. and Ca˜nette, I. (2011). Nonparametric estimation of distributions in random effects models. Journal
of Computational and Graphical Statistics 20 461-478.
11. Ma, Y., Hart, J.D. and Carroll, R.J. (2011). Density estimation in several populations with uncertain population membership. Journal of the American Statistical Association 106 1180-1192.
12. Sun, Y., Hart, J.D. and Genton, M. (2012). Nonparametric inference for periodic sequences. Technometrics
54 83-96.
1
235
13. Savchuk, O., Hart, J.D. and Sheather, S.J. (2013). One-sided cross-validation for nonsmooth regression functions. Journal of Nonparametric Statistics 25 889-904.
14. Sun, Y., Hart, J.D. and Genton, M. (2013). Improved nonparametric inference for multiple correlated periodic
sequences. Stat 2 197-210.
15. Zhan, D. and Hart, J.D. (2014). Testing equality of a large number of densities. Biometrika 101 449-464.
16. Gong, X., Gonzalez, R., McVay, D.A. and Hart, J.D. (2014). Bayesian probabilistic decline curve analysis
reliably quantifies uncertainty in shale well production forecasts. SPE Journal 19 1047-1057.
ii. Other Noteworthy Publications:
1. Hart, J.D. (1988). An ARMA type probability density estimator. Annals of Statistics 16 842-855.
2. Hall, P. and Hart, J.D. (1990). Bootstrap test for difference between means in nonparametric regression.
Journal of the American Statistical Association 85 1039-1049.
3. Hart, J.D. and Vieu, P. (1990). Data-driven bandwidth choice for density estimation based on dependent data.
Annals of Statistics 18 873-890.
4. Hart, J.D. (1991). Kernel regression estimation with time series errors. Journal of the Royal Statistical Society,
Series B 53 173-187.
5. Eubank, R. L. and Hart, J.D. (1992). Testing goodness-of-fit in regression via order selection criteria. Annals
of Statistics 20 1412-1425.
6. Hart, J.D. and Wehrly, T.E. (1993). Consistency of cross-validation when the data are curves. Stochastic
Processes and their Applications 45 351-361.
7. Hart, J.D. (1994). Automated kernel smoothing of dependent data by using time series cross-validation.
Journal of the Royal Statistical Society, Series B 56 529-542.
8. Eubank, R.L, Hart, J.D., Simpson, D. and Stefanski, L. (1995). Testing for additivity in nonparametric regression. Annals of Statistics 23 1896-1920.
9. Hart, J.D. (1997). Nonparametric Smoothing and Lack-of-Fit Tests. Springer-Verlag, New York.
10. Hart, J.D. and Yi, S. (1998). One-sided cross-validation. Journal of the American Statistical Association 93
620-631.
11. Aerts, M., Claeskens, G. and Hart, J.D. (1999). Testing the fit of a parametric function. Journal of the
American Statistical Association 94 869-879.
12. Aerts, M., Claeskens, G. and Hart, J.D. (2004). Bayesian-motivated tests of function fit and their asymptotic
frequentist properties. Annals of Statistics 32 2580-2615.
13. Hart, J.D. and Lee, C.-L. (2005). Robustness of one-sided cross-validation to autocorrelation. Journal of
Multivariate Analysis 92 77-96.
14. Ma, Y. and Hart, J.D. (2007). Constrained local likelihood estimators for semiparametric skew-normal distributions. Biometrika 94 119-134.
15. Hart, J.D., Koen, C. and Lombard, F. (2007). An analysis of pulsation periods of long-period variable stars.
Journal of the Royal Statistical Society, Series C 56 587-606.
Grants:
i. Last five years:
1. National Science Foundation, $170,665, ”New Methodology for Estimating Random Effects and for Statistical
Simulation Studies,” 2011-2015. (Sole P.I.)
ii. Other Noteworthy Grants:
1. National Science Foundation, $97,000, “Cluster-Based Bootstrapping in Multiple Hypotheses Testing,” 20062009. (Sole P.I.)
2
236
2. National Science Foundation, $80,000, “Model Selection and Tests of Model Fit,” 1999-2002. (Sole P.I.)
Awards and Honors:
1. Fellow of the Institute of Mathematical Statistics, 1994
2. Texas A&M University College of Science Distinguished Achievement Award in Teaching, 1995
3. Fellow of the American Statistical Association, 2001
4. Don Owen Award, 2007
5. Member of Editorial Boards:
Journal of the American Statistical Association (2008-2011, 1996-2002)
TEST (1997-2000)
Probability Theory and Related Fields (1992-1993)
Communications in Statistics (1991-1993)
6. Visiting Scholar:
Department of Applied Mathematics and Statistics, Colorado School of Mines (November 2013)
Department of Statistics, Limburgs University, Diepenbeek, Belgium (May 1999, June 2001)
Departamento de Matem´aticas, Universidade da Coru˜na, La Coru˜na, Spain (February 1998)
Institut de Statistique, Universit´e catholique de Louvain, Louvain-la-Neuve, Belgium (December 1997)
Service:
1. In 2014 organized session for Second International Society of Nonparametric Statistics Conference, Spain.
2. Chair, ASA Section on Nonparametrics, 2005.
3. Co-organizer of 2005 American Statistical Association Workshop entitled “Nonparametric Statistics: Frontier.”
4. Organized session for 2002 International Conference on Current Advances and Trends in Nonparametric Statistics,
Crete, Greece.
Ph.D. Students Supervised (8 most recent of 21):
1. Beverly Gaucher (2013) “Factor Analysis for Skewed Data and Skew-Normal Maximum Likelihood Factor Analysis.” (Co-chair with Thomas E. Wehrly)
2. Ying Sun (2011) “Inference and Visualization of Periodic Sequences.” (Co-chair with Marc Genton)
3. Qi Wang (2011) “Frequentist-Bayes Goodness-of-fit Tests.”
4. Olga Savchuk (2009) “Choosing a Kernel for Cross-Validation.” (Co-chair with Simon Sheather)
5. Nathaniel Litton (2009) “Deconvolution in Random Effects Models Via Normal Mixtures.”
6. Yi Qian (2005) “Topics in Multiple Hypotheses Testing.”
7. Juhee Song (2005) “Bootstrapping in a High Dimensional but Very Low Sample Size Problem.”
8. Suriani Pokta (2004) “Bayesian Model Selection Using Exact and Approximated Posterior Probabilities with Applications to Star Data.”
3
237
KEITH HATFIELD
Education:
University of Texas – Arlington
North Texas State University
BBA – Operations Research (1978)
MBA – Operations Research (1980)
Professional Experience
Hatfield Consulting Group
R.J. Stanley & Associates, Inc.
Ebasco Business Consulting
Principal – 1996 to present
Senior Consultant – 1983 to 1999
Consultant – 1981 to 1983
Appointments:
Lecturer
Department of Statistics, TAMU, Fall 2005 – present
Publications:
None
Grants in last five years:
None
Awards and Honors:
None
Service:
Coordinator of STAT 211 – Spring 2013 – present
1
238
JIANHUA HUANG
Education:
University of California at Berkeley
Beijing University, China
Beijing University, China
Appointments:
Professor
Associate Professor
Assistant Professor
Statistics
Probability and Statistics
Probability and Statistics
Ph.D. (1997)
M.A. (1992)
B.A. (1989)
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Statistics, University of Pennsylvania
2008-Present
2005-2008
1997-2004
Research Expertise:
Statistical learning, regularization methods, multivariate and high-dimensional data, functional and longitudinal data analysis, nonparametric and semiparametric methods, statistics application in astronomy, biology, business, economics and engineering
Publications:
i. Last five years: (selected from 48 refereed journal publications)
1. Pourhabib, A., Huang, J. Z. and Ding, Y. (2015). Short-term wind speed forecast using measurements from
multiple turbines in a wind farm. Technometrics, 57, to appear.
2. Xu, G., Wang, S. and Huang, J.Z. (2015). Nearly efficient robust estimation and inference based on focused
information model averaging. Scandinavian Journal of Statistic, 42, to appear.
3. Zhang, B., Sang, H. and Huang, J. Z. (2015). Full-Scale Approximations of Spatio-Temporal Covariance Models
for Large Datasets. Statistica Sinica, 25, 99–114.
4. Jung, Y., Huang, J. Z., Hu, J. (2014). Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA. Journal of American Statistical Association, 109, 1355–1367.
5. L. Zhang, H. Shen, and J. Z. Huang (2013). Robust Regularized Singular Value Decomposition for Two-way
Functional Data. Annals of Applied Statistics, 7, 540–1561.
6. Tian S. T., Huang, J.Z., Shen, H. and Li, Z. (2013). EEG/MEG Source Reconstruction with Spatial-temporal
Two-Way Regularized Regression. Neuroinformatics, 11(4): 477–93.
7. Sang, H. and Huang, J. Z. (2012). A full-scale approximation of covariance functions for large spatial data sets.
Journal of Royal Statistical Society, Series B, 74, 111–132.
8. J. Cao, J. Z. Huang, H. Wu (2012). Penalized nonlinear least squares estimation of time-varying parameters in
ordinary differential equations. Journal of Computational and Graphical Statistics, 21, 42–56.
9. Tian S. T., Huang, J.Z., Shen, H. and Li, Z. (2012). A two-way regularization method for MEG source reconstruction. Annals of Applied Statistics, 6, 1021–1046.
10. Chen, L. and Huang, J.Z. (2012). Sparse reduced-rank regression for simultaneous dimension reduction and
variable selection. Journal of American Statistical Association, 107, 1533–1545.
11. Xu, G. and Huang, J.Z. (2012). Asymptotic optimality and efficient computation of the leave-one-subject-out
cross-validation. Annals of Statistics, 40, 2765–3175.
12. Hays, S., Shen, H. and Huang, J.Z. (2012). Functional dynamic factor models with application to yield curve
forecasting. Annals of Applied Statistics, 6, 870–894.
13. Park, C., Huang, J.Z., Ji, J. and Ding, Y. (2012) Segmenting, inference and classification of partially overlapping
nanoparticles. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 507–522.
1
239
14. C. Park, J. Z. Huang, Y. Ding (2011). Domain decomposition approach for fast Gaussian process regression of
large spatial datasets. Journal of Machine Learning Research, 12, 1697–1728
15. H. Sang, M. Jun, J. Z. Huang (2011). Covariance approximation for large multivariate spatial datasets with an
application to multiple climate model errors. Annals of Applied Statistics, 5, 2519–2548.
16. Lee, M., Shen, H., Huang, J. Z. and Marron J. S. (2010). Biclustering via sparse singular value decomposition.
Biometrics, 66, 1087–1095.
17. Park C., Huang, J.Z. and Ding, Y. (2010). A computable plug-in estimator of minimum volume sets for novelty
detection. Operations Research, 58, 1469–1480.
18. Lee, S., Huang, J.Z. and Hu, J. (2010). Sparse logistic principal components analysis for binary data. The Annals
of Applied Statistics, 4, 1579–1601.
19. Cheng G. and Huang, J. Z. (2010). Bootstrap consistency for general semiparametric M-estimation. The Annals
of Statistics, 38, 2884–2915.
20. Zhou, L., Huang, J. Z., Martinez, J.G., Maity, A., Baladandayuthapani, V. and Carroll, R. J. (2010). Reduced
rank mixed effects models for spatially correlated hierarchical functional data. Journal of American Statistical
Association, 105, 390–400.
ii. Publications Before 2010: (selected from 28 refereed journal publications)
1. Huang, J. Z., Shen, H. and Buja, A. (2009). The analysis of two-way functional data using two-way regularized
singular value decompositions. Journal of American Statistical Association, 104, 1609–1620.
2. Wang L., Li, H. and Huang, J. Z. (2008). Variable selection in nonparametric varying-coefficient models for
analysis of repeated measurements. Journal of American Statistical Association, 103, 1556–1569.
3. Zhou, L., Huang, J. Z. and Carroll, R. J. (2008). Joint modeling of paired sparse functional data using principal
components. Biometrika, 95, 601–619.
4. Shen, H. and Huang, J. Z. (2008). Sparse principal component analysis via regularized low rank matrix approximation. Journal of Multivariate Analysis, 99, 1015–1034.
5. Shen, H. and Huang, J. Z. (2008). Interday forecasting and intraday updating of call center arrivals. Manufacturing & Service Operations Management, 10, 391–410.
6. Huang, J. Z., Liu, N., Pourahmadi, M., and Liu, L. (2006). Covariance selection and estimation via penalised
normal likelihood. Biometrika, 93, 85–98.
7. Huang, J. Z. (2003). Local asymptotics for polynomial spline regression. The Annals of Statistics, 31, 1600–1635.
8. Huang, J. Z., Wu., C. O., Zhou, L. (2002). Varying coefficient models and basis function approximations for the
analysis of repeated measurements. Biometrika, 89, 111–128.
9. Huang, J. Z. (2001). Concave extended linear modeling: A theoretical synthesis. Statistica Sinica, 11, 173–197.
10. Huang, J. Z. (1998). Projection estimation in multiple regression with application to functional ANOVA models.
The Annals of Statistics, 26, 242–272.
Grants in last five years:
i. Last five years:
1. Texas A&M University–NSFC Joint Research Program (2014-2015), $25,000, “Statistical Machine Learning and
Data Mining of the LAMOST Spectroscopic Survey,” (PI)
2. Air Force Office of Scientific Research (2013-2015), $611,152, “Dynamic, Data-Driven Modeling of Nanoparticle
Self Assembly Processes,” (co-PI; PI: Yu Ding)
3. National Science Foundation (2012-2015), $225,104, “Collaborative Research: New Developments for Analysis
of Two-way Structured Functional Data,” (PI)
4. King Abdullah University of Science and Technology (2012-2015), $275,000, “Computational and Statistical
Approaches for Protein Structure Prediction and Determination,” (co-PI; PI: Xin Gao)
2
240
5. Institute for Applied Mathematics and Computational Science, Texas A&M University (2011-2012), $25,000,
“Nonparametric Probabilistic Approach for Modeling the Local Protein Structure”, (PI)
6. National Science Foundation (2010-2014), $179,660, “A New Approach of Statistical Modeling and Analysis of
Massive Spatial Data Sets,” (co-PI; PI: Huiyan Sang)
7. Institute of Applied Mathematics and Computational Science, Texas A&M University (2010-2011), $25,000,
“Computationally Tractable Approximate Likelihood Inference for Irregularly Spaced Massive Spatial Data Sets,”
(PI)
8. National Science Foundation (2009-2013), $262,106, “Statistical Methods for Complex Functional Data,” (co-PI;
PI: Lan Zhou)
ii. Other Noteworthy Grants:
1. National Science Foundation (2009-2010), $10,000, “Conference on Statistical Methods for Complex Data” (PI)
2. National Science Foundation (2006-2009), $99,165, “Collaborative Research: Statistical Learning and Object
Oriented Data Analysis,” (PI)
3. National Science Foundation (2002-2005), $99,000, “Nonparametric and Semiparametric Methods for Longitudinal Data Analysis,” (PI)
Awards and Honors:
1. Best Application Paper for IIE Transactions (Quality/Reliability Engineering Focus Issue):
Park, C., Huang, J. Z., Huitink, D., Kundu, S., Mallick, B., Liang, H. and Ding, Y. (2012) A Multi-stage, Semiautomated procedure for analyzing the morphology of nanoparticles. IIE Transactions Special issue on Nanomanufacturing, 44, 507–522.
2. Fellow of the American Statistical Association
3. Fellow of the Institute of Mathematical Statistics
4. Member of Editorial Boards:
STAT—The ISI’s Journal for the Rapid Dissemination of Statistics Research (2015-Present).
Service:
1. Member of National Science Foundation Review Panel, multiple times
2. Referee for more than 30 journals
3. Chair of 2012 ICSA Applied Statistics Symposium Student Paper Award Committee, 2012
4. Member of the Organizing Committee for “Conference on Resampling Methods and High Dimensional Data,” College
Station, March 25-26, 2010
5. Member of the Organizing Committee for “Conference on Statistical Methods for Complex Data,” College Station,
March 14, 2009
Ph.D. Students Supervised:
Past Students (14):
Linxu Liu (2004), Naiping Liu (2004), Liangyue Zhang (2004), Zhihua Qiao (2005), Min Chen (2008), Seokho Lee (2009),
John Wagaman (2009), Saijuan Zhang (2010), Mehdi Maadooliat (2011), Chiwoo Park (2011), Huijun Pan (2011), Ganggang
Xu (2011), Shuo Feng (2014), Yuan Qu (2014).
Current Students (6):
Bohai Zhang, Nan Zhang, Senmao Liu, Ya Su, Shiyuan He, Kejun He.
Post-Docs Supervised:
Mehdi Maadooliat (2011-2013; Marquette University), Ganggang Xu (2012-2014; Binghamton University)
3
241
VALEN E. JOHNSON
Education:
Rensselaer Polytechnic Institute
University of Texas at Austin
The University of Chicago
Appointments:
Head
Professor
Ad Interim Division Head
Deputy Chairman
Professor
Adjunct Professor
Adjunct Professor
Technical Staff Member
Professor
Adjunct Professor
Director of Graduate Studies
Associate Professor
Director of Undergraduate Studies
Assistant Professor
Mathematics
Applied Mathematics
Statistics
B.S. (1981)
M.S. (1985)
Ph.D. (1989)
Department of Statistics, Texas A& M University
Department of Statistics,Texas A& M University
Division of Quantitative Sciences, MD Anderson Cancer Center
Department of Biostatistics, MD Anderson Cancer Center
Department of Biostatistics, MD Anderson Cancer Center
Department of Statistics, Rice University
Department of Statistics, Texas A&M University
Los Alamos National Laboratory
Institute of Statistics and Decision Sciences,Duke University
Department of Statistics, University of North Carolina
Institute of Statistics and Decision Sciences,Duke University
Institute of Statistics and Decision Sciences,Duke University
Institute of Statistics and Decision Sciences,Duke University
Institute of Statistics and Decision Sciences,Duke University
2014-Pres.
2012-Pres.
2011-2012
2007-2010
2004-2011
2005-2011
2007-2011
2001-2002
2000-2003
1999-2002
2000-2001
1993-2000
1995-1999
1989-1993
Publications:
i. Last five years (selected from 37 publications):
1. Hu, J. and Johnson, V.E. (2009), “Bayesian Model Selection Using Test Statistics,” Journal of the Royal
Statistical Society. Series B, 71, 143-158.
2. Banerjee, K., Chabris, C.F., Johnson, V.E., Lee, J., Tsai, F., Hauser, M.D. (2009), “General Intelligence
in Another Primate: Individual Differences across Cognitive Task Performance in a New World Monkey
(Saguinus oedipus),” PLoS ONE, 4 (6): e5883.doi:10.1371/journal.pone.0005883.
3. Johnson, V.E. and Cook, J.D. (2009), “Bayesian Design of Single-Arm Phase II Clinical Trials with Continuous Monitoring,” Clinical Trials, 6, 217-226.
4. Hu, J. and Johnson, V.E. (2009), “Log-Linear Models for Gene Association,” Journal of the American Statistical Association, 104, 597-607.
5. Johnson, V.E. and Rossell, D. (2010), “On the use of non-local prior densities for default Bayesian hypothesis
tests,” Journal of the Royal Statistical Society. Series B, 72, 143-170.
6. Cao, J., Moosman, A., and Johnson, V.E. (2010), “A Bayesian Chi-Squared Goodness of Fit Test for Censored
Data Models,” Biometrics, 66, 426-434.
7. Wang, X.S., Cleeland, C.S., Mendoza, T.R., Yun, Y.H., Wang, Y., Okuyama, T., Johnson, V.E. (2010), “Impact of Cultural and Linguistic Factors on Symptom Reporting by Patients with Cancer,” Journal of the National Cancer Institute, 102, 732-738.
8. Johnson, V.E. (2010), “Bayesian Aggregation Error?,” International Journal of Safety and Reliability, 4, 359365.
9. Reese, C.S, Wilson, A.G., Guo, J., Hamada, M., and Johnson, V.E., (2011), “A Bayesian Model for Integrating
Multiple Sources of Lifetime Information in System-Reliability Assessments,” Journal of Quality Technology,
43, 127-141.
1
242
10. Johnson, V.E. and Rossell, D. (2012), “Bayesian Variable Selection in High-dimensional Settings,” Journal
of the American Statistical Association, 107, 649-660.
11. Yuan, Y. and Johnson, V.E. (2012), “Goodness-of-fit diagnostics for Bayesian hierarchical models,” Biometrics, 68, 156-164.
12. Amici, F., Barney, B., Johnson, V.E., Cail, J., and Aurelli, F. (2012), “A Modular Mind? A Test Using
Individual Data from Seven Primate Species,” PLoS ONE, e51918. doi:10.1371/journal.pone.0051918.
13. Johnson V.E. (2013), “Uniformly most powerful Bayesian tests,” Annals of Statistics, 41, 1716-1741
14. Johnson, V.E. (2013), “Revised standards for statistical evidence,” Proceedings of the National Academy of
Sciences, 110(48), 19313-19317.
15. Cai, C., Yuan, Y., and Johnson, V.E. (2013), “Bayesian Adaptive Phase II Screening Design for Combination
Trials,” Clinical Trials, 10, 353-362.
16. Johnson, V.E. (2013), “On Numerical Aspects of Bayesian Variable Selection in High and Ultrahigh Dimensional Settings,” Bayesian Analysis, 7, 1-18.
17. Liu S., Yuan Y., Castillo R., Guerrero T., and Johnson V.E. (2014), “Evaluation of Image Registration Spatial
Accuracy Using a Bayesian Hierarchical Model,” Biometrics, 70(2), 366-377.
18. Jun M., Katzfuss M., Hu J. and Johnson V.E. (2014), “Assessing fit in Bayesian models for spatial processes,”
Environmetrics, 25(8), 584-595.
19. Barney B., Amici F., Aureli F., Call J. and Johnson, V.E. (2015), “Joint Bayesian Modeling of Binomial and
Rank Data for Primate Cognition,” Journal of the American Statistical Association, in press.
ii. Other Noteworthy Publications (selected from over 100 peer-reviewed publications):
1. Johnson, V.E. and Albert, J. (1999), Ordinal Data Models, Springer-Verlag: New York.
2. Johnson, V.E. (2003), Grade Inflation: A Crisis in College Education. Springer-Verlag, New York.
3. Johnson, V.E. (1994), “A Model for Segmentation and Analysis of Noisy Images,” Journal of the American
Statistical Association, 89, 230-241.
4. Johnson, V.E. (1996), “Studying Convergence of Markov Chain Monte Carlo Algorithms Using Coupled
Sampling Paths,” Journal of the American Statistical Association, 91, 154-166.
5. Johnson, V.E. (1996), “On Bayesian Analysis of Multirater Ordinal Data: An Application to Automated
Essay Grading,” Journal of the American Statistical Association, 91, 42-51.
6. Johnson, V.E. (1998), “A Coupling-Regeneration Scheme for Diagnosing Convergence in Markov Chain
Monte Carlo Algorithms,” Journal of the American Statistical Association, 93, 238-248.
7. Johnson, V.E., Deaner, R.O. and van Schaik, C.P. (2002), “Bayesian Analysis of Multi-Study Rank Data with
Application to Primate Intelligence Ratings,” Journal of the American Statistical Association, 8-17.
8. Johnson, V.E. (2004), “A Bayesian χ2 Test for Goodness-of-Fit,” Annals of Statistics, 32, 2361-2384.
9. Johnson, V.E. (2005), “Bayes Factors Based on Test Statistics,” Journal of the Royal Statistical Society, Series
B, 67(5), 689-701.
10. Johnson, V.E. (2008), “A Statistical Analysis of the NIH Peer Review System,” Proceedings of the National
Academy of Sciences, 105 (32), 11076-11080.
Grants in last five years:
i. Last five years:
1. Principal Investigator, “Consistent Model Selection in the p n Setting,” NIH R01, 2011-2015.
2. Biostatistics Core Director, “Symptom Mechanisms of Multiple Myeloma and Its Therapy,” (Principal Investigator: Charles Cleeland), NIH P01, 2008-2013.
2
243
3. Collaborating Investigator, “Reducing the Symptom Burden Produced by Aggressive Cancer Therapies,” Principal Investigator: Charles Cleeland), NIH R01, 2008-2011.
4. Collaborating Investigator, “Statistical methods for genomic analysis of heterogeneous tumors,” (Principal
Investigator: Wenyi Wang), NIH R01, 2015-2019.
ii. Other Noteworthy Grants:
1. Principal Investigator, NIH Center for Scientific Review Intergovernment Personnel Agreement “Analysis of
Scientific Review Group Ratings,” 2005-2006.
2. Principal Investigator, Los Alamos National Laboratory Contract in response to proposal 58947-SOL-02,
“Bayesian Methodology for Reliability Analyses,” 2002.
3. Principal Investigator, NSF grant “Discrete Models for High-Level Image Analysis,” 1998-2001.
4. Principal Investigator, NSF grant“Scientific Computing Research Environment for Mathematical Sciences,”
1995.
5. Principal Investigator, NIH FIRST Award “Reconstruction and Analysis of Emission Computed Tomography
Data,” 1992-1997.
Awards and Honors:
1. Fellowships:
Elected member of the International Statistical Institute (ISI)
Fellow of the American Statistical Association
Fellow of the Royal Statistical Society
2. Member of Editorial Boards and Award Committees:
Co-Editor, Bayesian Analysis, 2010-2014
Associate Editor, J. of the American Stat. Assoc. (JASA) (1992-1996, 2011-Present)
Associate Editor, Bayesian Analysis (2006-2010)
Associate Editor, IEEE Transactions on Medical Imaging, 1993-2002
Chair, Lindley Award Committee, 2008
Char or Member, Savage Award Committee, 2004-2007
Treasurer, International Society for Bayesian Analysis, 1998-2001
Savage Award for Outstanding Thesis in Bayesian Statistics and Econometrics, 1989
Doctoral Students Supervised:
1. Alyson Wilson, “Statistical Models for Shapes and Deformations,” 1995. Alyson won the Savage Award for the
best thesis in Bayesian statistics and econometrics.
2. Colin McCulloch, “High-level Image Understanding Through Bayesian Hierarchical Models,” 1998. Colin was one
of four finalists for the 1999 Savage Award.
3. Jacob Laading, “Practical Methodology for Inclusion of Modality-Specific Modifications in a Hierarchical Bayesian
Deformation Model,” 1999.
4. Stephen Ponisciak, “Bayesian Analysis of Teacher Effectiveness,” 2002.
5. Sining Chen, “On Automated Bayesian Image Analysis,” 2002.
6. Adarsh Joshi, “Bayesian Model Selection for High-Dimensional High-Throughput Data,” Department of Statistics,
Texas A&M University, 2010 (while a faculty member at M.D. Anderson Cancer Center).
7. Brad Barney, “Bayesian Joint Modeling of Binomial and Rank Response Data,” Department of Statistics, Texas
A&M University, 2011 (while a faculty member at M.D. Anderson Cancer Center).
8. Scott Goddard, “Restricted Most Powerful Bayesian Tests,” Department of Statistics, Texas A&M University.
3
244
EDWARD R. JONES
Education:
Texas A&M University – Commerce
Virginia Polytechnic & State Univ.
Virginia Polytechnic & State Univ.
Computer Science
Statistics
Statistics
Appointments:
2010-Pres Executive Professor
2008-2010 Senior Statistician
2002-2008 Senior Statistical Advisor
1992-2003 Assoc. Professor
1985-1989 Vice President
1984-1985 Dir. of Consulting
1977-1984 Senior Statistician
1975-1977 Asst. Professor
Dept. of Statistics, Texas A&M University
Stata, Inc., College Station, TX
Visual Numerics, Inc., Houston, TX
Dept. of Math. & Computer Sci., Texas A&M University-Corpus Christi
Jones Reilly & Assoc., Cupertino, CA
Enhansys, Inc., Cupertino, CA
Chevron Research Company, Richmond, CA
Dept. of Statistics, Texas A&M University
B.S. w/honors (1972)
M.S. (1974)
Ph.D. (1976)
Presentations and Workshops: Past 2 years
i. Invited
1. Presentation for IAMCS Machine Learning on Text Analytics, Feb 4, 2014
2. 2-day Workshop – Econometrics using Stata, Aug 21-22; Mexico City
ii. Contributed
1. Half-Day Workshops
2. Text Analytics - CSP-2014, Tampa, FL; Feb 20, 2014
3. Text Analytics - SESUG, Myrtle Beach, NC; Oct 19, 2014
4. Text Analytics - SCSUG, Austin, TX; Nov 12, 2014
5. Text and Social Media Analysis – CSP-2015, New Orleans, LA; Feb 21, 2015.
iii. Papers
1. Text Analytics using High Performance SAS, MWSUG, Chicago, IL; Oct 7, 2014
2. Text Analytics – Today and Tomorrow, INFORMS 2014, San Francisco, CA, Nov 10, 2014.
Grants in last five years:
i. University Grants – Submitted (co-investigator)
1. (2013) 2 submitted for $32,222
2. (2014) 3 submitted for $325,514
3. (2015) 1 submitted for $137,555
ii. Contracts
1. (2012-2015) Dept. of Veterans Affairs ($21,600/Yr)
2. (2014) Capital One ($59,000)
3. (2015-2018) Dept. of Treasury ($199,000 over 3 years)
Awards and Honors: Please annotate as space allows
i. 2014 – Mentored 1st and 3rd place teams in Capital One Modeling Competition
ii. 2012 – Mentored 1st and 2nd place team in Capital One Modeling Competition
iii. (2015-2017) Elected Director on the Executive Committee, ASA Section on Statistical Consulting
iv. 2013 – Text Analytics Workshop selected for sponsorship by ASA Board of Directors
Service: Please annotate as space allows
Sessions Organized and Work at National Meetings of the American Statistical Association (ASA)
1
245
i.
Organizing Committee and Organizer for Analytics Track – Conference on Statistical Practice 2014 –
Orlando, FL.
ii. Organizing Committee and Organizer for Analytics Track – Conference on Statistical Practice 2015 – New
Orleans, CA.
iii. Organizing Committee and Organizer for Analytics Track – Conference on Statistical Practice 2016 – San
Diego, CA.
Students Supervised (2014-2016):
i. MS expected in 2016
1. Cindy Czako
2. Giewee Hammond
3. Ziad Katrib
4. Yoel Kluk
5. Pablo Ormachea
ii. MS expected in 2015
1. William C. Dean
2. Aaron D. Agnew
3. Salsawit Shifarraw
4. Katrina Williams
5. James M. Bergeron
6. Steve J. Bowden
7. Lauren Engle
8. Danny Leonard
9. Erin Parrott
10. Bora Tarhan
11. Bryce Durgin
iii. MS graduated in 2014
1. Kurt B. Johnson*
2. Shiva S. Dhandapani
3. Wenling Zhang
4. Qian Zhou
5. Colm Walsh*
6. James Joseph*
*Committee chair or co-chair
Collaboration with TAMU System Researchers (Fall 2014 – Spring 2015)
1. (2015-) Sakhila, Banu, – Dept. of Veterinary Integrative Biosciences
2. (2015-) Snider, Erin, – TAMU Bush School of Government
3. (2014-) Bevans, John, DVM – College of Veterinary Medicine and Central Texas Specialty Hospital
4. (2014) Goldberg, – Dept. of Geography (GIS Study for Cervical Cancer in New Mexico)
5. (2014) Masabni, Joseph, – Dept. of Horticultural Sciences
6. (2014) Morris, Theresa, – Dept. of Sociology
7. (2014) Moyna, Irene, – Dept. of Hispanic Studies
8. (2014) Goldberg, Daniel – Dept. of Geography, College of Geosciences
9. (2014) Lacey, Ron and Faulkner, Brock – AgriLife College Station
10. (2014) Swiger, Sonja, – AgriLife Stephenville, TX
11. (2014) Keith, Verna, M. – Dept. of Sociology
12. (2014) Taylor, Lori, – Dept. Educational Administration
2
246
MIKYOUNG JUN
Education:
Seoul National University
University of Chicago
Statistics
Statistics
Appointments:
Associate Professor (with Tenure)
Adjunct Associate Professor
Assistant Professor
Adjunct Assistant Professor
Visiting Scientist
B.S. (1999)
Ph.D. (2005)
Department of Statistics, Texas A&M University
Department of Biostatistics, UT MD Anderson Cancer Center
Department of Statistics, Texas A&M University
Department of Biostatistics, UT MD Anderson Cancer Center
National Center for Atmospheric Research
Sep 2012 - Present.
Sep 2012 - Aug 2013
Aug 2005 - Aug 2011
Apr 2012 - Aug 2012
Aug 2005 - Dec 2005
Publications:
i. Last five years:
1. Jun, M., Szunyogh, I., Genton, M.G., Zhang, F., Bishop, C.H. (2011). A statistical investigation of the
sensitivity of ensemble based Kalman filters to covariance filtering. Monthly Weather Review, Volume 139,
pp. 3036-3051.
2. Jun, M. (2011). Nonstationary cross-covariance models for multivariate processes on a globe. Scandinavian
Journal of Statistics, Vol 38, pp. 726-747.
3. Sang, H., Jun, M., Huang, J.Z. (2011). Covariance approximation for large multivariate spatial datasets with
an application to multiple climate model errors. Annals of Applied Statistics, Volume 5, pp. 2519-2548.
4. Vaughan, A., Jun, M., Park, C. (2012). Statistical inference and visualization in scale-space for spatially
dependent images. Journal of Korean Statistical Society, Volume 41, pp. 115-135.
5. Jun, M., Genton, M.G. (2012). A test for stationarity of spatio-temporal random fields on planar and spherical
domains. Statistica Sinica, Volume 22, pp. 1737-1764.
6. Park, S., Navratil, S., Gregory, A., Bauer. A., Srinath, I., Jun, M., Szonyi, B., Nightingale, K., Anisco,
J., Ivanek, R. Generic Escherichia coli contamination of spinach at the preharvest level: The role of farm
management and environmental factors. Applied and Environmental Microbiology, Volume 79, pp. 43474358.
7. Jun, M., Park, E.S. (2013). Multivariate receptor modeling for spatially correlated multi-pollutant data. Technometrics, Volume 55, pp. 309-320.
8. Roh, S., Genton, M.G., Jun, M., Szunyogh, I., Hoteit, I. (2013). Observation Quality Control with a Robust
Ensemble Kalman Filter. Monthly Weather Review, Volume 141, pp. 4414-4428.
9. Park, S., Navratil, S., Gregory, A., Bauer, A., Srinath, I.,Szonyi, B., Nightinglgale, K., Ancisco, J., Jun, M.,
Han, D., Lawhon, S., Ivanek, R. (2014). Farm management, environment and weather factors jointly affect
the probability of spinach contamination with generic Escherichia Coli at the preharvest level. Applied and
Environmental Microbiology, Volume 80, pp. 2504-2515.
10. Jun, M. (2014). Mat´ern-based nonstationary cross-covariance models for global processes. Journal of Multivariate Analysis, Volume 128, pp. 134-146.
11. Jun, M., Katzfuss, M., Hu, J. and Johnson, V.E. (2014). Assessing fit in Bayesian models for spatial processes.
Environmetrics, Volume 25, pp. 584-595.
12. Jeong, J., Jun, M.. (2015). A class of Mat´ern-like covariance functions for smooth processes on a sphere.
Spatial Statistics, Volume 11, pp. 1-18.
1
247
13. Park, S., Navratil, S., Gregory, A., Bauer, A., Srinath, I., Szonyi, B., Nightingale, K., Anciso, J., Jun, M.,
Han, D., Lawhon, S., and Ivanek, R.. (2015+). Count of generic Escherichia coli on spinach at the preharvest
level determined by the interplay of ambient temperature, precipitation, farm management and environmental
factors. Applied and Environmental Michro Biology, Accepted.
ii. Other Noteworthy Publications:
1. Jun, M. (2011). Discussion of “An explicit link between Gaussian fields and Gaussian Markov random fields:
The stochastic partial differential equation approach” by Finn Lindgren, H˚avard Rue and Johan Lindstr¨om.
Journal of the Royal Statistical Society, Series B, 73, p. 478.
2. Jun, M., Stein, M.L. (2008). Nonstationary covariance models for global data. Annals of Applied Statistics,
Volume 2, pp. 1271-1289.
3. Jun, M., Knutti, R., Nychka, D.W. (2008). Spatial Analysis to Quantify Numerical Model Bias and Dependence: How Many Climate Models Are There? Journal of the American Statistical Association, Volume 103,
pp. 934-947.
4. Jun, M., Knutti, R., Nychka, D.W. (2008). Local eigenvalue analysis of CMIP3 climate model errors. Tellus,
60A, pp. 992-1000.
5. Jun, M., Stein, M.L. (2007). An Approach to Producing Space-time Covariance Functions on Spheres. Technometrics, Volume 49, No. 4, pp. 468-479.
6. Jun, M., Stein, M.L. (2004). Statistical Comparison of Observed and CMAQ Modeled Daily Sulfate Levels.
Atmospheric Environment, Volume 38, Issue 27, pp. 4427-4436.
Grants in last five years:
1. National Science Foundation, $100,000, “In-depth development and assessment of covariance models for multivariate nonstationary processes on a sphere”, (sole-) PI, 2012-2015.
2. National Science Foundation, $75,000, “Nonstationary spatial-temporal covariance models for multivariate processes on a globe”, (sole-) PI, 2009-2012.
3. National Science Foundation, $1,030,000, “Non-Gaussian statistical analysis of large climate datasets and simulations”, co-PI, 2006-2010.
4. KAUST GRP Award, $1,250,000, Investigator, 2008-2013.
Awards and Honors:
1. Elected member of the International Statistical Institute (ISI)
2. Member of Editorial Boards:
STAT, (2012-Present).
Journal of Agricultural, Biological, and Environmental Statistics. (JABES) (2011-Present).
Journal of the Korean Statistical Society. (2008-Present).
3. Visiting Scholar:
Institute for Applied Mathematics, University of Heidelberg, October-December 2013.
Department of Statistics, Seoul National University, June-September 2013.
Center for Integrating Statistical and Environmental Science, University of Chicago, Summer 2006 & June-September
2007.
Service:
Sessions Organized and Work at National and International Meetings:
1. Program committee for JSM, Seattle, 2015.
2
248
2. Short course committee for ICSA-KISS joint meeting, Portland, 2014.
3. Program committee for ICSA-KISS joint meeting, Portland, 2014.
4. Co-organizer of summer school in Data Assimilation, NCAR, 2015.
5. Co-organizer of a workshop on spatial statistics, Texas A&M University, 2015.
6. Co-organizer of the workshop on Statistical methods for Climate problem, IAMCS, Texas A&M University, 2012.
7. Co-organizer of the workshop on Data assimilation in the Geosciences, IAMCS, Texas A&M University, 2009.
8. Scientific advisory board, Spatial Statistics 2013 conference, June 2013.
9. Organizer of invited session:
JSM 2015, 3rd IMS-APRM 2014, ISI WSC 2013, IMS-APRM 2012, ENAR 2011, 12th International Conference
on Statistics, Combinatorics, Mathematics and Applications 2005
10. Organizer of invited poster session for JSM 2015
11. Organizer of a topic-contributed session (or special topic session):
JSM 2014, ISBA 2012, JSM 2010,
12. ASA/ENVR student award committee for JSM, 2006 - 2008.
Other nothworthy service:
1. Node director, STATMOS, 2014-Present.
2. Associate Director, Program in Spatial Modeling, Department of Statistics, Texas A&M University, 2009-2012.
3. National Science Foundation review panel 2012.
Courses taught:
STAT 211 (Principle of statistics I) (undergraduate)
STAT 647 (Spatial statistics) (graudate, on-campus course as well as a course for business analytics program)
STAT 685 (ATMO 685) (graduate, joint course with ATMO)
Students Supervised:
Soojin Roh (2014), Ph.D, Texas A&M University (jointly with Marc Genton)
Dissertation: Robust Ensemble Kalman Filter and Localization for Multiple State Variables
Robert Philbin (2014), M.S, Texas A&M University
Forrest Womack (2014), M.S, Texas A&M University
Paul Reed (2012), M.S, Texas A&M University
Justin Chown (2011), M.S, Texas A&M University (jointly with Mike Sherman)
Post-Docs Supervised:
Dr. Myoungji Lee, Texas A&M University, 2012-2014. (jointly with Marc Genton)
3
249
MATTHIAS KATZFUSS
Education:
The Ohio State University
The Ohio State University
Statistics
Statistics
Appointments:
Assistant Professor
Akademischer Rat auf Zeit (Postdoc)
M.S. (2008)
Ph.D. (2011)
Texas A&M University
Universit¨at Heidelberg
2013-Pres.
2011-2013
Refereed Publications:
i. Last five years:
1. Jun, M., Katzfuss, M., Hu, J., and Johnson, V.E. 2014. Assessing fit in Bayesian models for spatial processes.
Environmetrics, 25(8), 584–595.
2. Gneiting, T., and Katzfuss, M. 2014. Probabilistic forecasting. Annual Review of Statistics and its Application,
1, 125–151.
3. Heaton, M.J., Katzfuss, M., Berrett, C., and Nychka, D.W. 2014. Constructing valid spatial processes on the
sphere using kernel convolutions. Environmetrics, 25(1), 2–15.
4. Nguyen, H., Katzfuss, M., Cressie, N., and Braverman, A. 2014. Spatio-temporal data fusion for remotesensing applications. Technometrics, 56(2), 174–185.
5. Katzfuss, M. 2013. Bayesian nonstationary spatial modeling for very large datasets. Environmetrics, 24(3),
189–200.
6. Katzfuss, M., and Cressie, N. 2012. Bayesian hierarchical spatio-temporal smoothing for very large datasets.
Environmetrics, 23(1), 94–107.
(Student Paper Award, First Place, ASA Section on Statistics and the Environment)
7. Katzfuss, M., and Cressie, N. 2011. Spatio-temporal smoothing and EM estimation for massive remotesensing data sets. Journal of Time Series Analysis, 32(4), 430–446.
8. Heaton, M.J., Katzfuss, M., Ramachandar, S., Pedings, K., Gilleland, E., Mannshardt-Shamseldin, E., and
Smith, R. 2011. Spatio-temporal models for large-scale indicators of extreme weather. Environmetrics, 22(3),
294–303.
Grants in last five years:
i. Last five years:
1. Visiting Researcher Grant ($13,156) at the National Center for Atmospheric Research (NCAR), awarded by
the Research Network for Statistical Methods for Atmospheric and Oceanic Sciences (2015)
Awards and Honors:
1. Poster Award, Fifth IMS–ISBA Joint Meeting, Chamonix, France (2014)
2. Young Investigator Travel Award ($550), Fifth IMS–ISBA Joint Meeting (2014)
3. Student Paper Award, First Place ($1,000), American Statistical Association, Section on Statistics and the Environment (2011)
1
250
4. Ransom & Marian Whitney Award for Best Dissertation Research ($400), Department of Statistics, The Ohio State
University (2011)
5. Young Investigator Travel Award ($650), Fourth IMS–ISBA Joint Meeting (2011)
6. Ransom & Marian Whitney Award for Outstanding Research Associate ($150), Department of Statistics, The Ohio
State University (2010)
7. Edward G. Mayers Travel Fellowship ($1,000), Division of Natural and Mathematical Sciences, The Ohio State
University (2010)
8. Edward J. Ray Travel Award for Scholarship and Service ($750), Council of Graduate Students, The Ohio State
University (2010)
9. Fulbright Scholarship (2007 – 2008)
10. German Academic Exchange Service (DAAD) Semester Scholarship (2007)
Service:
1. Organizing Committee for the Workshop on Spatial Statistics at Texas A&M University (2015)
2. Committees at Department of Statistics, Texas A&M University
Faculty Recruitment Committee (2014 – 2015)
Department Advisory Committee (2014 – 2015)
Website Redesign Committee (2014)
3. Session Organizer, “Spatial Statistics for Big Environmental Datasets” (Invited Session), Joint Statistical Meetings,
Montr´eal, Canada (2013)
4. Session Organizer, “Spatial Statistics for Very Large Environmental Data Sets” (Topic-Contributed Session), Joint
Statistical Meetings, San Diego, CA (2012)
5. Student-Body President, Department of Statistics, OSU (2009 – 2011)
6. Member, Student Advisory Board, Wiley Series in Probability and Statistics (2009 – 2011)
Students Supervised:
Jaehong Jeong (2015 (expected)), Texas A&M University: Committee Member (main advisor: Mikyoung Jun)
Patrick Schmidt (2013), Master’s, Universit¨at Heidelberg (with Tilmann Gneiting): “Estimation of loss functions” (2013)
2
251
ELIZABETH YOUNG KOLODZIEJ
Education:
University of Georgia
University of Georgia
Texas A&M University
Appointments:
Instructor
Senior Lecturer
Statistics
Statistics
Statistics
B.S. (2003)
M.S. (2005)
Ph.D. (2010)
Department of Mathematics, Robert Morris University Fall 2010-Spring 2012
Department of Statistics, Texas A&M University
Summer 2012-Present
Presentations:
Panel Member, “Analytics and Big Data Survey Review and Interpretation: Panel and Audience Discussion,”
Conference on Statistical Practice, American Statistical Association, 2015
Awards and Honors:
Distinguished Graduate Student Award for Excellence in Teaching
Fellow, Graduate Teaching Academy
Graduate Merit Fellowship, Texas A&M University
Outstanding Graduate Student Teaching Award, University of Georgia
2010
2009
2005
2005
Service:
Member, Undergraduate Degree Committee
2014-2015
Students Supervised:
Committees served on:
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Kishan Raj (2015 - pending), M.S., INEN
Zhou Wang (2015 - pending), M.S., ELEN
Teresa Barnett (2015 - pending), M.S., STAT
Jonathan Presto (2015 - pending), M.S., STAT
Daniela Sakamoto (2015 - pending), M.S., STAT
Jeremy Fergason (2015 - pending), M.S., STAT
Jin Do (2015 - pending), M.S., STAT
Nicholas Darschewski (2015 - pending), M.S., STAT
Ulagappa Abinaya (2014), M.S., INEN
Kenneth Reed (2014), M.S., MATH
Yonatan Negash (2013), M.S., STAT
1
252
HWA CHI LIANG
Education:
Soochow University, Taiwan
University of Texas at Austin
University of New Mexico
Appointments:
Senior Lecturer
Associate Professor
Assistant Professor
Business Mathematics
Mathematics
Statistics
B.A. (1979)
M.A. (1987)
Ph.D. (2003)
Department of Statistics, Texas A&M University
Department of Mathematics & Statistics, Washburn University
Department of Mathematics & Statistics, Washburn University
Fall, 2014 – Pres.
2010 – 2014
2004 – 2010
Publications:
none in the past 5 years
Grants in last five years:
none
Collaboration
Currently collaborate with Professor Jenn-Tai Liang at the Department of Petroleum Engineering, Texas A&M
University in developing proposals that involve statistical applications for research in petroleum engineering.
Awards and Honors:
Member of Editorial Boards:
Missouri Journal of Mathematical Sciences (MJMS) (2013-Present).
Service:
Washburn University Service Record (2004 – 2014)
Supervisor of Math Tutor Center
Evaluation committee for the Dean of College of Arts and Sciences
Faculty Senate
Mentor for new faculty
College Faculty Council (CFC)
The CFC Curriculum subcommittee
The Interdisciplinary Studies Committee
Students Supervised:
1
253
JAMES P. LONG
Education:
Columbia University, New York, USA
University of California, Berkeley, USA
Appointments:
Assistant Professor
Statistics and Mathematics
Statistics
Department of Statistics, Texas A&M University
B.A. (2008)
Ph.D. (2013)
2013-Pres.
Publications:
i. Last five years:
1. (with A. N. Morgan, J. W. Richards, T. Broderick, N. R. Butler, J. S. Bloom) Rapid, machine-learned resource
allocation: Application to high-redshift GRB follow-up. The Astrophysical Journal (2012) 746, 170.
2. (with J.S. Bloom, N. El Karoui, J. Rice, J.W. Richards) Classification of poorly time sampled light curves of
periodic variable stars. Book chapter in Astrostatistics and Data Mining (2012) 2, 163 – 171.
3. (with N. El Karoui, J. A. Rice, J.W. Richards, and J. Bloom) Optimizing Automated Classification of Periodic
Variable Stars in New Synoptic Surveys. Publications of the Astronomical Society of the Pacific (2012) 124.
280 – 295.
4. (with J.W. Richards, D.L. Starr, H. Brink, A.A. Miller, J.S. Bloom, N.R. Butler, J.B. James & J. Rice) Active learning to overcome sample selection bias: Application to photometric variable star classification. The
Astrophysical Journal (2012). 744. 192.
5. (with V. Tilvi, C. Papovich, S.L. Finkelstein, M. Song, M. Dickinson, H.C. Ferguson, A.M. Koekemoer, M.
Giavalisco, B. Mobasher.) Rapid Decline of Lyα Emission toward the Reionization Era. The Astrophysical
Journal (2014) 794, 5.
6. (with B. Salmon, C. Papovich, et al.) The Relation between Star Formation Rate and Stellar Mass for Galaxies
at 3.5 z 6.5 in CANDELS The Astrophysical Journal (2015) 799, 183.
Student Committees:
Ph.D.
• Shiyuan He (Statistics, Thesis Committee, 2015)
• Yi Yang (Physics & Astronomy, Thesis Committee, 2015)
M.S.
• Ryan Oelkers (Physics & Astronomy, Thesis Committee, 2014)
• Brett Salmon (Physics & Astronomy, Thesis Committee, 2015)
• Leo Alcorn (Physics & Astronomy, Thesis Committee, 2015)
1
254
MICHAEL LONGNECKER
Education:
Michigan Technological University
Western Michigan University
Florida State University
Mechanical Engineering
Statistics
Statistics
B.S. (1968)
M.S. (1972)
Ph.D. (1976)
Appointments:
Interim Department Head
Associate Department Head
Director of Consulting Center
Professor
Visiting Associate Professor
Associate Professor
Assistant Professor
Visiting Assistant Professor
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Statistics, Univ. of Wisconsin-Madison
Department of Statistics, Texas A&M University
Institute of Statistics, Texas A&M University-CS
Department of Statistics, Florida State University
2004-2005
2000-Current
2000-2012
1992-Current
1989-90
1984-1992
1977-84
1976-77
Publications:
i. Last five years:
1. (with S.B. Sleeba, P. Teel, and O. Strey) Host selection by questing female Amblyomma maculatum Koch, to
cattle feeding male ticks in southern Texas, Veterinary Parasitology, 2010, 172, 105-108.
2. (with B.W. Hopkins and P. Pietrantonio) Transcriptional overexpression of CYP6B8/CYP6B28 and CYP6B9
is a mechanism associated with cypermethrin survivorship in field collected Helicoverpazea (Lepidoptera:
Noctuidae) moths, Pest Management Science, (2010), 67, 21-25.
3. (with M.T. Nunez De Gonzalez, W.N. Osburn, M.D. Hardin, H.K. Garg, N.S. Bryan, J.T. Keeton) Survey
of residual nitrite and nitrate in conventional and organic/natural/uncured/indirectly cured meats available at
retail in the United States, Agricultural and Food Chemistry, (2012), 60, 3981-3990.
4. (with Hyeogsun Kwon, Hsiao-Ling Lu, and Patricia Pietrantonio) Role in diuresis of a calcitonin receptor
(GPRCAL1) expressed in a distal-proximal gradient in renal organs of the mosquito Aedes aegypti (L.), PLOS
ONE, (2013) 7.
5. (with D.R. Tolleson, G. Carstens, T. Welsh, P. Teel, O. Strey, S. Prince, and K. Banik) Plane of Nutrition by
Tick Burden Interaction in Cattle: Effect on Growth and Metabolism, Journal of Animal Science, (2013) 90,
3442-3450.
6. (with J.K. Tomberline, T.L. Crippen, A.M. Tarone, B. Singh, K. Adams, Y.H. Rezenom, M.E. Benbow, M.
Flores, J.L. Pechal, D.H. Russell, R.C. Beier, T.K. Wood), Interkingdom responses of flies to bacteria mediated
by fly physiology and bacterial quorum sensing, Animal Behaviour, (2013) 84(6), 1449-1456.
7. (with D.R. Tolleson, G. Carstens, T. Welsh, P. Teel, O. Strey, S. Prince, and K. Banik) Plane of Nutrition
by Tick Burden Interaction in Cattle: Effect on fecal composition , Journal of Animal Science (2013), 91,
3658-3665.
8. (with M. Flores and J.K. Tomberline) Effects of temperature and tissue type on Chrysomay ruifacies (Diptera:
Calliphoriadae)(Macquart) development, Forensic Science International, (2014), 245, 24-29.
9. (with J. Thinakaran, E. Peirson, C. Tamborindeguy, D. Henne) Settling and ovipositional behavior of the
potato psyllid on solanaceous hosts under field and laboratory conditions, Journal of Economic Entomology,
(2015), To appear.
1
255
10. (with M.T. Nunez De Gonzalez, W.N. Osburn, M.D. Hardin, H.K. Garg, N.S. Bryan, J.T. Keeton) A survey of
nitrite and nitrate concentrations in conventional and organic-labeled raw vegetables at retail, Journal of Food
Science, (2015), To appear.
ii. Textbook:
1. R. L. Ott and M. Longnecker (2015). An Introduction to Statistical Methods and Data Analysis, 7th Ed.,
Cengage Learning, Belmont, CA.
Grants in last five years:
i. Last five years:
1. (with P. Teel) National Center for Foreign Animal and Zoonotic Disease, $45,000, An Application of Weather
Dynamics to Predict Population Changes and Enhanced IPM Stategies for the Gulf Coast Tick, 2013-2014,
(Co-P.I.).
ii. Other Noteworthy Grants:
1. (with J. Walker, R. Kott, A. Cibilis) USDA, $65,000, Enhancing the Use of Small Ruminants to Control
Noxious Weeds, 2004-2007, (Co-P.I.).
Awards and Honors:
1. National Mu Sigma Rho Statistics Education Award, 2011
2. Elected Fellow of American Statistical Association, 2009
3. Western Michigan University Alumni Achievement Award, 2007
4. Finalist for the Texas A&M University Presidential Professor for Teaching Excellence, $10,000 Award, 2004
5. The Association of Former Students of Texas A&M University, Faculty Distinguished Award in Teaching, 1994
6. The Association of Former Students of Texas A&M University, College of Science, Distinguished Teaching Award,
1982
National Service:
1. Associate Editor: Journal of the American Statistical Assoc. (JASA), (1989-92)
2. Associate Editor: The American Statistician, (1987-89)
3. Member of The Committee on Membership Retention and Recruitment, (2010-2014)
4. Co-Chair of The Committee on Membership Retention and Recruitment, (2010-2014)
Students Supervised: (All at Texas A&M University)
Frederic Che-Yuen, Ph.D., (1982)
Dissertation: Nonparametric Tests for Homogeneity of the Marginal Distributions of Paired Data
Edgar Wayne Richardson, Ph.D., 1986
Dissetation: Asymptotic Normality of the Parameters of Certain Mixtures of Discrete and Continuous Distributions
Dennis W. King, Ph.D., 1988
Dissertation: Nonparametric Procedures for Process Control
2
256
Randy Bartlett, Ph.D., 1993
Dissertation: Measures of Capability Under Nonstandard Conditions
Diane Davies, Ph.D., 1994
Dissertation: Statistical Process Control for Correlated Data
Qinli Yue, Ph.D., 1996
Dissertation: Chemometric Calibration and Partial Least Squares
Abeer Al-Khouli, Ph.D., 1999
Dissertation: Robust Estimation and Bootstrap Testing for the Delta Distribution with Applications in the Marine Science
Yibing Zhong, Ph.D., 2000
Dissertation: The Spatial Modeling of a Mixture Distribution
Chair of over 100 Statistics M.S. Committees, 1980-2014
Member of over 80 Statistics Ph.D. Committees, 1980-2014
Member of over 350 non-Statistics M.S. and Ph.D. Committees, 1980-2014
3
257
BANI K. MALLICK
Education:
Presidency College, Calcutta, India Statistics B.S. (1986)
Calcutta University, Caluctta,India Statistics M.S. (1988)
University of Connecticut
Statistics Ph.D. (1994)
Appointments:
Distinguished University Professor
Department of Statistics, Texas A&M University
Professor
Department of Statistics, Texas A&M University
Director
Center for statistical Bioinformatics, Texas A&M University
Director, Bayesian Bioinformatics Lab Texas A&M University
Adjunct Professor of Biostatistics
MD Anderson Cancer center
Adjunct Professor
University of Michigan
Associate Professor
Department of Statistics, Texas A&M University
Assistant Professor
Department of Statistics, Texas A&M University
Permanent Lecturer
Department of Mathematics, Imperial College, London
Publications (Last 5 years):
2011-Present
2003-2011
2010-Present
2006-Present
2006-Present
2008-2010
2000-2003
1998-2000
1994-1998
1. Kim, H.-M., Ryu, D., Mallick, B. K., and Genton, M. G. (2014), “Mixtures of skewed Kalman filters”, Journal of
Multivariate Analysis, 123, 228-251.
2. Chakraborty, A., De, S., Bowman, K., Sang, H., Genton, M. G., and Mallick, B. (2015), “An adaptive spatial model for
precipitation data from multiple satellites over large regions,” Statistics and Computing, 25, 389-405.
3. Baladandydayuthapani, V., Talluri, R., Ji, Y., Coombes, K., Hennessy, B., Davies, M. and Mallick, B. (2014) “Bayesian
sparse graphical models for classification with application to protein expression data”, Annals of Applied Statistics, 8,
3, 1443-1468.
4. Mondal, A., Mallick, B., Efendiev, Y. and Datta-Gupta, A. (2014), “Bayesian uncertainty quantification for subsurface
inversion using multiscale hierarchical model”, Technometrics, 56:3, 381-392.
5. B. A Konomi, H. Sang, B. K Mallick (2014) “ Adaptive Bayesian nonstationary modeling for large spatial datasets
using covariance approximations”, Journal of Computational and Graphical Statistics, 23 (3), 802-829.
6. Sarkar, A., Mallick, B. and carroll, R. (2014), “Bayesian semiparametric regression in the pesence of conditionally
heteroscedastic measurement and regression errors”, Biometrics, to appear.
7. Sarkar, A., Mallick, B, Staudenmayer, J., Pati, D. and Carroll, R (2014), “ Bayesian semiparametric density deconvolution in the presence of conditionally heteroscedastic measurement errors”, Journal of Computational and Graphical
Statistics, to appear.
8. L. Zhang, V. Baladandayuthapani, B.K. Mallick, G.C., Manyam, P.A. Thompson, M.L. Bondy and K. Do (2014)
Bayesian hierarchical structured variable selection with application to molecular inversion probe studies in breast cancer. Journal of the Royal Statistical Society: Series C, 63: 595620.
9. Mondal, A., Mallick, B., Efendiev, Y. and Datta-Gupta, A. (2014), “Bayesian uncertainty quantification for subsurface
inversion using multiscale hierarchical model”, 56, 3, 381-392, Technometrics.
10. L. Zhang and B.K. Mallick. (2013) “Inferring gene networks from discrete expression data” Biostatistics, 14(4): 708722.
11. Chakraborty, A., Mallick, B., McClareren, R., Kuranz, C. and Drake, P. (2013) “Spline based emulators for radiative
shock experiments with measurement error”, 108, 411-428 , Journal of the American Statistical Association[Featured
Article].
12. Ryu, D., Liang, F. and Mallick, B. (2013) “A Dynamically particle filter with radial basis function networks for sea
surface temperature modeling”, 108, 111-123, Journal of the American Statistical Association.
13. Xun, X., Cao, J., Mallick, B., Carroll, R. and Maity, A. (2013) “Parameter estimation of partial differential equation
model”, 108, 1009-1020, Journal of the American Statistical Association.
14. Konomoi, A, Park, C., Huang, J., Huitink, D., Kundu, S., Liang, H. and Ding, Y., Mallick, B. (2013) “Bayesian
modeling for analyzing the morphology of gold nanoparticles”, 7, 2, 640-668, Annals of Applied Statistics.
1
258
15. Bhadra, A. and Mallick, B. (2013) , “Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis”, 69, 2, 447-457, Biometrics [Featured Article].
16. Zhao, K., Valle, D., Popescu, S., Zhang, X., & Mallick, B. (2013). Hyperspectral remote sensing of plant biochemistry
using Bayesian model averaging with variable and band selection. Remote Sensing of Environment, 132, 102-119.
17. Hartman, B., Talukdar, D. and Mallick, B. (2012) “Investigating cross-country influence dynamics in new product
diffusion process”. Annals of Applied Statistics, 6, 625-651.
18. Chakraborty, S., Ghosh, M. and Mallick, B. (2012) “Bayesian Nonlinear Regression for Large p Small n Problems”.
Journal of Multivariate Analysis, 108, 28-40.
19. Park, C., Huang, J.Z., Huitink, D., Kundu, S., Mallick, B.K., Liang, J., Ding, Y. (2011), A multi-stage, semi-automated
procedure for analyzing the morphology of nanoparticles, IIE Transactions; Special Issue on Nano Manufacturing.
20. Xun, X., Mallick, B., Carroll, R. and Kuchment, P. (2011) “A Bayesian approach to the detection of small low emission
sources”. Inverse Problems, 27.
21. Parzen, M., Ghosh, S., Lipsitz, S., Fitzmaurice, Ibrahim, J. and Mallick, B. (2011) “A generalized linear mixed model
for longitudinal binary data with a marginal logit link function”. Annals of Applied Statistics, 5, 1,449-467.
22. Ryu, D., Li, E. and Mallick, B. (2011), “Bayesian nonparametric regression analysis when covariates are subjectspecific parameters in a random effect model for longitudinal measurement”, Biometrics, 67, 2, 454-466.
23. Lobach, I., Mallick, B., Carroll, R. (2011) “Bayesian analysis of case-control data with gene environment interaction
and error in measurement of environmental covariates”,Statistics and its interface, 4, 305-315.
24. Sturino, J., Zorych, I., Mallick, B., Pokusaeva, K., Carroll, R. (2011) “Statistical Methods for Comparative Phenomics
using High-throughput Phenotype Microarrays,” The intrenational journal of Biostatistics, 6.
25. McClarren, R., Ryu, D., Drake, P., Bingham, D., Fryxell, B., Mallick, B., Torralva, B. (2011) “A Physical informed
emulator for laser-driven radiation shock simulations”, to appear, Reliability engineering and system safety.
26. Holloway, J., Bingham, D., Drake, P., Mallick, B., Nair, V., Ryu, D., Zhang, Z. (2011) “Predictive modeling of a
radiative shock system”Reliability engineering and system safety (to appear).
27. Stripling, H., Adams, M., McClarren, R. and Mallick, B. (2011) “The method of manufactured universes for validating
quantification methods”, Reliability engineering and system safety (to appear).
28. Dhavala, S., Datta, S., Mallick, B., Carroll, R. and Adams, G. (2010) “Bayesian modeling of MPSS data: Gene
expression analysis of Bovine Salmonella infection”,Journal of the American Statistical Association, 105, 956-967.
29. Xia, H., Ding, Y. and Mallick, B. (2010) “Bayesian hierarchical model for combining misaligned two-resolution metrology data” , IIE transactions, 43, 242-258 [Featured Article].
30. Ghosh, S. and Mallick, B. (2010) “A Hierarchical Bayesian Spatio-temporal Model for Extreme Precipitation Events”.
Environmetrics, 22, 2, 192-204.
31. Sinha S, Mallick B.K, Kipnis V, Carroll R.J. (2010) “Semiparametric Bayesian Analysis of Nutritional Epidemiology
Data in the Presence of Measurement Error”. Biometrics, 66, 444-454.
32. Huitink, D., Kundu, S., Park, C., Mallick, B., Huang, J. and Liang, H. (2010) “Nanoparticle shape evolution identified
through multivariate statistics”, Journal of Physical Chemistry, 114, 5596-5600.
33. Maity, A. and Mallick B. (2010) “Proportional Hazards Regression Using Bayesian Kernel Machines”, In Bayesian
Modeling Issues in Bioinformatics and Biostatistics, Wiley (to appear).
34. Efendiev, Y., Datta Gupta, A., Hwang, K., Ma, X. and Mallick, B. (2010) “Bayesian Partition Models for Subsurface
Characterization”, In Large-scale inverse problems and quantification of uncertainty, Wiley (to appear).
35. Ray, S. and Mallick, B. (2010), “Model based principal component analysis: Bayesian approaches,” In Frontier of
Statistical Decision Making and Bayesian Analysis, Springer.
36. Mondal, A., Efendiev, Y,Mallick, B. and Datta Gupta, A. (2010)“Bayesian Uncertainty Quantification for Flows in Heterogeneous Porous Media using Reversible Jump Markov Chain Monte Carlo Methods”, Advances in Water resources,
33, 241-256.
37. Efendiev, Y., A. Datta-Gupta, X. Ma, and B. Mallick (2009), Efficient sampling techniques for uncertainty quantification in history matching using nonlinear error models and ensemble level upscaling techniques, Water Resour. Res., 45,
W11414, doi:10.1029/2008WR007039.
2
259
38. Fu, W., Mallick, B. and Carroll, R. (2009) “Why do we observe misclassification errors smaller than the Bayes error”,
Journal of statistical computation and simulation,79, 717-722.
Books Published in last five years:
1. Mallick, B., Gold, D. and Baladandanayak, V. (2010) Bayesian analysis of gene expression data, Wiley International.
2. Biegler, L., Ghattas, O., Keyes, D., Mallick, B., Tenorio, L., Waanders, V. and Willcox, K. (2011) Large scale inverse
problems and quantification of uncertainty, John Wiley and Sons Ltd, U.K.
3. Dey, D., Ghosh, S. and Mallick, B.(2011) Bayesian Modeling Issues in Bioinformatics and Biostatistics, Chapman and
Hall/CRC.
Grants in last five years:
1. NSF, $690,699 “CMG: Multiscale data integration using facies based hierarchical models”, PI, 2007-2012
2. Norman Hackerman Advanced research program (ARP), ($150,000).“Bayesian Hierarchical Models for Integrating
Multi-resolution Information”, PI, 2008-2010
3. NSF, $769,053 “Bayesian Data Mining Approaches for Biological Threat Detection”, PI, 2009-2012
4. NIH, $862,000 “Bayesian models for gene expression with microarray data”, PI, 2005-2010
5. DOE, $347,714 “Bayesian uncertainty quantification in predictions of flows in Highly heterogeneous media and its
applications to the CO2 sequestration”, Co-PI 2012-2016
6. Department of Energy (DOE), $3.5 million “Center for Radiative Hydrodynamics (CRASH)”, Co-I, 2008-2013
7. Department of Energy (DOE), $3.4 million, “Center for Predictive computational Sciences (PECOS)”, Co-I, 2008-2013
8. King Abdullah University of Science and Technology (KAUST) Global Research Partnership Center Award, Co-I,
2008-2013
9. National Cancer Institute (NCI), “Measurement error, Nutrition and cancer”, Merit Award, Co-I, 2005-2015
Awards and Honors:
Fellow of the American Association for the Advancement of Science (AAAS)
Fellow of the Institute of Mathematical Statistics (IMS)
Association of Former Students Distinguished Achievement in Research, Texas A&M University, 2006
Fellow of the American Statistical Association (ASA)
Elected member of International Statistical Institute (ISI)
Fellow of the Royal Statistical Society (RSS)
Outstanding Researcher Award, 2007: International Indian Statistical Association
Member of Editorial Boards:
Journal of Computational and Graphical Statistics (JCGS) (2004-Present)
Biostatistics (2009-Present)
SIAM/ASA Journal on Uncertainty Quantification (2013-Present)
Chemometrics (2013-Present)
Journal of Applied Mathematics and Stochastic Analysis (2005-2009)
Service:
Member of SHRP2: Safety Technical Coordinating Committee (TCC), Transportation Research Board, The National Academies
Member of Executive Committee of Institute for Applied and Computational Science (IAMCS)
Reviewer of Canada Research Chair Program
Reviewer of EPSRC Research Proposals, UK
Reviewer: Initial Period Review of Professors, Oxford University, UK
President (2002-2008), Southeast Texas Chapter
Students Supervised: (Total 25 Students, List of a few recent students with current employers)
Souparno Ghosh (2009), Assistant Professor, Texas Tech
Soma Dhavala (2010), Associate Reserach Scientist, Dow Agroscience
Brian Hartman (2010), Assistant Professor, University of Connecticut
Bledar Konomoi (2011), Assistant Professor, University of Cincinnati
Anirban Mondal (2011), Assistant Professor, Case Western Reserve University
Lin Zhang (2012) Assistant Professor, University of Minnesota
Abhra Sarkar (2014), Postdoctorate Fellow, Duke University
Post-Docs Supervised: (Total 10, List of recent ones with current employer)
Anindya Bhadra (2010-2012), Assistant Professor, Purdue University; Avishek Chakraborty (2012-2014), Assistant Professor, University of Arkansas; and Supratik Kundu (2012-2014) Assistant Professor, Emory University.
3
260
URSULA U. MÜLLER
Education:
Freie Universität Berlin, Germany
Universität Bremen, Germany
Universität Bremen, Germany
Appointments:
Professor
Assoc. Professor
Assist. Professor
Visiting Assist. Prof.
Assist. Professor
Visiting Professor
Post-doc. Researcher
Mathematics
Mathematics
Mathematics
Diplom
Dr. rer. nat.
Habilitation
(1993)
(1997)
(2005)
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Dept. of Math. & Statistics, Arizona State University
Dept. of Math., Universität Bremen, Germany
Dept. of Math., Universität Siegen, Germany
Dept. of Math., University of British Columbia
2013-present
2009-2013
2006-2009
2001-2002 and 2003-2004
1998-2001, 2002-2003, and 2004-2006
Oct. 2002-Feb.2003
Jan.-July 1998
Publications:
i. Last five years:
1.
(with A. Schick and W. Wefelmeyer) 2015. Estimators in step regression models. To appear in: Statist.
Probab. Lett., 10 pp.
2.
(with W. Wefelmeyer) 2014. Estimating a density under pointwise constraints on the derivatives. Math.
Meth. Statist., 23, 201-209.
3.
(with A. Schick and W. Wefelmeyer) 2014. Testing for additivity in partially linear regression with possibly
missing responses. J. Multivariate Anal., 128, 51-61.
4.
(with I. Van Keilegom) 2014. Efficient quantile regression with auxiliary information. Contemporary
Developments in Statistical Theory, Springer Proceedings in Mathematics & Statistics, 68, 365-374.
5.
(with A. Schick and W. Wefelmeyer) 2014. Efficient estimators for alternating quasi-likelihood models. J.
Indian Statist. Assoc., 52, 1-17.
6.
(with J. Chown) 2013. Efficiently estimating the error distribution in nonparametric regression with
responses missing at random. J. Nonparametr. Statist., 25, 3, 665-677.
7.
(with A. Schick and W. Wefelmeyer) 2013. Non-standard behavior of density estimators for functions of
independent observations. In: Stochastic Modeling Techniques and Data Analysis International Conference,
Comm. Statist. Theory Methods, 42, 16, 2291-2300.
8.
(with A. Schick and W. Wefelmeyer) 2013. Variance bounds for estimators in autoregressive models with
constraints. Statistics, 47, 3, 477-493.
9.
(with J. Wei, R.J. Carroll, I. Van Keilegom and N. Chatterjee) 2013. Robust Estimation for Homoscedastic
Regression in the Secondary Analysis of Case-Control Data. J. R. Stat. Soc. Ser. B Stat. Methodol., 75, 185206.
10. (with H.L. Koul and A. Schick) 2012. The transfer principle: A tool for complete case analysis. Ann. Statist.,
40, 3031-3049.
11. (with I. Van Keilegom) 2012. Efficient parameter estimation in regression with missing responses. Electron.
J. Stat., 6, 1200-1219.
12. 2012. Estimating the density of a possibly missing response variable in nonlinear regression. J. Statist. Plann.
Inference, 142, 1198-1214.
13. (with A. Schick and W. Wefelmeyer) 2012. Estimating the error distribution function in semiparametric
additive regression models. J. Statist. Plann. Inference, 142, 552-566.
1
261
14. (with A. Schick and W. Wefelmeyer) 2011. Optimal plug-in estimators for multivariate distributions with
conditionally independent components. J. Nonparametr. Statist., 23, 1031-1050.
ii. Other noteworthy publications:
1.
2009. Estimating linear functionals in nonlinear regression with responses missing at random. Ann. Statist.,
37, 2245-2277.
2.
2007. Weighted least squares estimators in possibly misspecified nonlinear regression. Metrika, 66, 39-59.
3.
(with A. Schick and W. Wefelmeyer) 2006. Efficient prediction for linear and nonlinear autoregressive
models. Ann. Statist., 34, 2496-2533.
4.
(with G. Osius) 2003. Asymptotic normality of goodness-of-fit statistics for sparse Poisson data. Statistics,
37, 119-143.
5.
2000. Nonparametric regression for threshold data. Can. J. Stat., 28, 301-310.
Grants in last five years:
1.
National Science Foundation, $114,000, “Efficient Estimation in Semiparametric Regression with Possibly
Incomplete Data”, 2009-2012, Principal Investigator
Awards and Honors:
1.
2.
Member of editorial board:
Statistics and Probability Letters (2011-present).
Elected member of the International Statistical Institute (ISI),
Service (last five years)
Sessions organized and work at national and international meetings:
1.
2.
Organized and chaired invited sessions at the 2012 Joint Statistical Meetings (San Diego, CA), and the 2013
IISA conference (Chennai, India).
Chaired sessions at Joint Statistical Meetings (Miami Beach, 2011, Montreal, 2013), the 2012 Open
Conference on Probability and Statistics (Mainz, Germany), the 2014 ISNPS conference (Cadiz, Spain) and
the 2014 IASSL conference (Colombo, Sri Lanka 2014).
Students Supervised:
1.
Justin Chown (2014), Ph.D, Texas A&M University
Dissertation: New approaches in testing common assumptions for regressions with missing data.
2.
Scott D. Crawford (2012), Ph.D, Texas A&M University
Dissertation: Efficient estimation in a regression model with missing responses.
3.
Member of 10 Ph.D and 24 M.S. advisory committees at Texas A&M University since 2006
2
262
MOHSEN POURAHMADI
Education:
College of Statistics, Tehran, Iran
Michigan State University
Michigan State University
Appointments:
Professor (Visiting)
Professor
Professor
Professor (Visiting)
Director
Associate Professor
Associate Professor (Visiting)
Assistant Professor (Visiting)
Assistant Professor
Statistics
Statistics
Statistics
B.S. (1973)
M.S. (1977)
Ph.D. (1980)
Department of Statistics, University of Chicago
Department of Statistics,Texas A& M University
Division of Statistics, NIU
Department of Statistics, University of Chicago
Division of Statistics, NIU
Division of Statistics, NIU
University of California, Davis
University of N. Carolina, Chapel Hill
Northern Illinois University (NIU)
Fall, 2014
2008-Pres.
1989-2008
2001-2002
1994-2001
1985-1989
1987-1988
1984-1985
1981-1985
Publications:
i. Last five years:
1. (with M.Daniels) Modeling covariance matrices via partial correlations. Journal Multivariate Analysis, (2009),
100, 2352-2363.
2. Modeling covariance matrices: The GLM and regularization perspectives, Stat. Sciences, (2011), 26, 369-387.
3. (with M. Maddooliat and J. Z. Huang) Robust estimation of the correlation matrix of longitudinal data. Statistics and Computing, (2011), 23, 1-12.
4. (with P. Dellaportas) The Cholesky-GARCH models with application to finance. Statistics and Computing,
(2012), 22, 849-855.
5. (with P. Kohli and T. Garcia) Regressograms and mean-covariance models for incomplete longitudinal data.
The American Statistician, (2012), 66, 85-91.
6. (with J. Huang, M. Chen and M. Maadooliat) A cautionary note on generalized linear models for covariance
of unbalanced longitudinal data. Journal of Statistical Planning and Inference, (2012), 142, 743-751.
7. (with F. Ye, T. Garcia and D. Ford) Extension of a Negative Binomial GARCH Model: Analyzing the Effects
of Gasoline Price and VMT on DUI Fatal Crashes in Texas. Journal of Transportation Research, (2012), 2279,
31-39.
8. High-Dimensional Covariance Estimation, John-Wiley, 2013.
9. (with L. Chen and M. Madooliat) Regularization of Multivariate Regression Models with Skew Errors, Journal
of Statistical Inference and Planning, (2014), 125-139.
10. (with P. Kohli) Some Prediction Problems for Stationary Random Fields with Quarter-Plane Past, Journal of
Multivariate Analysis, (2014), 112-125.
ii. Other Noteworthy Publications:
1. Journal of Statistical Planning and Inference, Vol. 140, December 2010, Guest Editor (with Richard Davis),
Special Issue in honor of Emmanuel Parzen’s 80th Birthday and Retirement from the Department of Statistics,
Texas A&M University.
1
263
2. Pourahmadi, M., Daniels, M.J. and Park, T. (2007). Simultaneous modeling of the Cholesky decompositions
of several covariance matrices. J. of Multivariate Analysis, 98, 568-587.
3. Huang, J., Liu, N., Pourahmadi, M. and Liu, L. (2006). Covariance selection and estimation via penalized
normal likelihood. Biometrika, 93, 85-98.
4. Wu, W.B. and Pourahmadi, M. (2003). Nonparametric estimation of large covariance matrices of longitudinal
data. Biometrika, 90, 831-844.
5. Pourahmadi, M. (2000). Maximum likelihood estimation of generalized linear models for multivariate normal
covariance matrix. Biometrika, 87, 425-435.
6. Pourahmadi, M. (1999). Joint mean-covariance models with applications to longitudinal data: Unconstrained
parameterisation. Biometrika, 86, 677-690.
7. Daniels, M.J. and Pourahmadi, M. (2002). Bayesian analysis of covariance matrices and dynamic models for
longitudinal data. Biometrika, 89, 553-566.
8. Pourahmadi, M. (2001). Foundations of Time Series Analysis and Prediction Theory. Wiley, New York.
9. Mohanty, R. and Pourahmadi, M. (1996). Estimation of the generalized prediction error variance of a multiple
time series. J. of Amer. Stat. Assoc., 91, 294-299.
Grants in last five years:
i. Last five years:
1. National Science Foundation, $120,000, ”Sparse Graphical Models for Multivariate Time Series”, 2013-2015.
2. National Science Foundation, $195,000, ”Generalized Linear Models for Large Correlation Matrices via Partial Correlations”, 2009-2012.
ii. Other Noteworthy Grants:
1. National Science Foundation, $60,000, ”Model-Based Classification of Longitudinal and Functional Data”,
2005-2007.
2. National Science Foundation, $82,000, “Simultaneous Modelling of Several Large Covariance Matrices”,
2003-2005.
3. NSF-SCREMS (Scientific Computing Research Environments in Mathematical Sciences (1997-98) $75,000.
4. National Security Agency (1996-1998), $42,000, “Topics on Non-Gaussian and Nonlinear Time Series.”
5. Air force Office of Scientific Research (1988-1991), $37,000, “Analysis of NonGaussian, Nonlinear Time
Series with Long Memory.”
6. National Science Foundation (1986-1989), $23,967, “Autoregressive Representation of Nonstationary Processes.”
7. National Science Foundation (1983-1986), $18,000, “Cesaro Summability of the Linear Predictor of a Stationary Time Series.”
Awards and Honors: Please annotate as space allows
1. Elected member of the International Statistical Institute (ISI),
2. Fellow of the American Statistical Association,
3. Member of Editorial Boards:
Journal of the American Statistical Assoc. (JASA) (2014-Present).
Journal of Business and Economics Statistics (2012-Present).
Statistics and Probability Letters (2008-2014).
Electronic Journal of Statistics (2010-2012).
Journal of Applied Mathematics and Stochastic Analysis (2005-2009).
2
264
4. Visiting Scholar:
Department of Mathematics, Hiroshima University, March 2012.
Department of Statistics, Pontificia Universidad Catolica de Chile, May 2011.
Melbourne Business School, University of Melbourne, Australia, (May-June, 2009).
Australian School of Business, University of New South Wales, Australia, (July, 2009).
Department of Mathematics, Hokkaido University, Japan (July-August 2005 and March, 2007)
Department of Mathematics and Statistics, Kuwait University, Kuwait (May, 2004).
Service: Please annotate as space allows
Sessions Organized and Work at National and International Meetings:
1. Chair of the organizing committee for the 2012 NSF-NBER Conference on Time Series Analysis, Texas A&M
University (Oct. 26-27).
2. Member of the International Organizing Committee of the Workshop on Correlated Data Modeling, Torino, Italy,
2004.
3. Co-chair (with Ken Berk) of the 31st Symposium on the Interface: Computing Science and Statistics, June, 1999,
Schaumburg, IL
4. Organizer of the Longitudinal Data Analysis Workshop, DeKalb, IL, Nov. 6-7, 1997.
5. Chair of the Local Arrangements Committee (LAC) for the joint statistical meetings in Chicago in August 1996.
Students Supervised:
Ranye Sun (2014), Ph.D, Texas A&M University
Dissertation: Reduced Rank Multivariate Regression and Generalized Matrix Decomposition using Thresholding Methods.
Priya Kohli (2012), Ph.D, Texas A&M University
Dissertation: Prediction of Stationary Random Fields. (Co-avdviser, Willa Chen)
Lianfu Chen (2011), Ph.D, Texas A&M University
Dissertation: Regularization of Parameters in Multivariate Linear Regression.
M. Al-Rawwash, Ph.D. in Probability and Statistics, Northern Illinois University, 2001.
Tsair-Chuan Lin, Ph.D. in Probability and Statistics, 1996.
Radha Mohanty, Ph.D. in Probability and Statistics, 1992.
Post-Docs Supervised:
Dr. Bahram Tarami, Shiraz University, Iran, 2000-2001.
Dr. Yukio Kasahara, The University of Tokyo and The Hokkaido University, Japan, Summers 2004 and 2006.
3
265
HUIYAN SANG
Education:
Peking University, Beijing, China
Duke University
Appointments:
Associate Professor
Assistant Professor
Mathematics and Applied Mathematics
Statistics
Texas A&M University
Texas A&M University
B.S. (2004)
Ph.D. (2008)
2014-present
2008-2014
Publications:
i. Last five years:
1. (with M. Genton and S. Padoan) Multivariate max-stable spatial processes, Biometrika, (2015),
doi: 10.1093/biomet/asu066.
2. Composite likelihood for extreme values, Book chapter in Extreme Value Modeling and Risk Analysis: Methods and Applications, (2015), Chapman Hall/CRC.
3. (with W. Han, M. Sheng, J. Li, and S. Cui) Efficient learning of statistical primary patterns via Bayesian
network, Proceedings: IEEE International Conference on Communications (ICC), (2015), London, UK.
4. (with B. Zhang and J. Z . Huang) Full-scale approximations of spatio-temporal covariance models for large
datasets, Statistica Sinica, (2015), 25, 99-114.
5. (with A. Chakraborty, S. De, K. Bowman, M. Genton and B. K. Mallick) Hierarchical spatial model for
precipitation data from multiple satellites, Statistics and Computing, (2015), 25, 389-405.
6. (with B. Konomi and B. K. Mallick) Adaptive Bayesian nonstationary modeling for large spatial datasets using
covariance approximations, Journal of Computational and Graphical Statistics, (2014), 23, 802-829.
7. (with M. Genton) Tapered composite likelihood for spatial extremes, Spatial Statistics, (2014), 8, 86-103.
8. (with J. Z. Huang) A full-scale approximation of covariance functions for large spatial data sets, Journal of
the Royal Statistical Society, Series B, (2012), 4, 111-132.
9. (with M. Jun and J. Z. Huang) Covariance approximation for large mutivariate spatial datasets with an application to multiple climate model errors, Annals of Applied Statistics, (2011), 5, 2519-2548.
10. (with M. Genton and Y. Ma) On the likelihood function of Gaussian max-stable processes indexed by Rd , d ≥
1, Biometrika, (2011), 8, 481-488.
11. (with A. E. Gelfand) Continuous spatial process For extreme values, Journal of Agricultural, Biological and
Environmental Statistics, (2010), 15, 49-65.
12. (with A. M. Latimer, S. Banerjee, E. Mosher, and J. A. Silander), Hierarchical models facilitate spatial analysis
of large data sets: A case study on invasive plant species in the northeastern United States, Ecological Letters,
(2009),12, 144-154.
13. (with A. O. Finley, S. Banerjee, and A. E. Gelfand), Improving the performance of predictive process modeling
for large datasets, Computational Statistics and Data Analysis, (2009), I53, 2873-2884.
14. (with A. E. Gelfand) Hierarchical Modeling for Extreme Values Observed over Space and Time. Environmental and Ecological Statistics, (2009), 16, 407-426.
ii. Other Noteworthy Publications:
1
266
1. (with A. E. Gelfand, C. Lennard, G. Hegerl and B. Hewitson) Interpreting self organizing maps through spacetime models, Annals of Applied Statistics, (2008), 2,1194-1216.
2. (with S. Banerjee, A. E. Gelfand and A. O. Finley) Gaussian predictive process models for large spatial
datasets, Journal of the Royal Statistical Society, Series B, (2008), 70, 825-848.
Grants in last five years:
i. Last five years:
1. National Science Foundation, co-PI, $459,200, “Large-Scale Statistical Learning based Spectrum Sensing and
Cognitive Networking”, 2014-2017
2. National Science Foundation, PI, $179,660, “A New Approach of Statistical Modeling and Analysis of Massive Spatial Data Sets”, 2010-2014,
3. IAMCS-KAUST Innovative Research Award, PI, $25,000, “Spatio-temporal Models of Extreme Values: An
Application to Sea Surface Temperatures in the Red Sea”, 2013-2014
4. IAMCS-KAUST Innovative Research Award, co-PI, $35,000, “Computationally Tractable Approximate Likelihood Inference for Irregularly Spaced Massive Spatial Data Sets”, 2010-2011
5. IAMCS-KAUST Innovative Research Award, PI, $20,000, “Arbitrary Feature Identification in Protein Mass
Spectrometry Using Prior Knowledge of Feature Interrelationships”, 2008-2009.
6. KAUST GRP award, Investigator, “Institute for Applied Mathematics and Computational Science (IAMCS)”,
2008-2013
Awards and Honors: Please annotate as space allows
1. ISBA Young Researcher Award, Google, 2012
2. NSF INI Travel Award, National Science Foundation, 2008
3. Member of Editorial Boards:
STAT (2013-Present).
Teaching:
Courses Taught
1. Statistics 211: Principles of Statistics (I). Fall 2008, Spring and Fall 2009, Spring 2010, Spring 2011, Fall 2012,
Spring 2013, Fall 2014
2. Statistics 610: Distribution Theory. Fall 2010
3. Statistics 611: Statistical Inference. Spring 2013
4. Statistics 647: Spatial Statistics. Fall 2013, Fall 2014
Service: Please annotate as space allows
Sessions Organized and Work at National and International Meetings:
1. Session Organizer for: IMS-China, 2015; SRCOS, 2012; ICSA, 2012; ISBA, 2012.
2. Co-organizer for the IAMCS workshop on Spatial Statistics and Climate Sciences, 2012.
3. Co-organizer of the Spatial Statistics Workshop, TAMU, TX, Jan, 2015.
2
267
Students Supervised:
Xinxin Zhu (2013), Ph.D, Texas A&M University
Dissertation: Wind Forecasting for Power System Operation
Blemar Konomi (2011), Ph.D, Texas A&M University
Dissertation: Bayesian Modeling of Spatial and Spatial-Temporal Data
Bohai Zhang(expected in 2015), Ph.D, Texas A&M University
Dissertation: Computational Methods for Large Spatial and Spatial-Temporal Data
Post-Docs Supervised:
Dr. Irma Hernandez, UC-Berkeley, CA, 2014-present.
3
268
HENRIK SCHMIEDICHE
Education:
Texas A&M University
Texas A&M University
Texas A&M University
Appointments:
Lecturer
Senior Lecturer
Director IT
Computer Science
Statistics
Statistics
B.S. (1987)
M.S. (1989)
Ph.D. (1993)
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
College of Science, Texas A&M University
1993-1997
1997-Pres.
2014-Pres.
Current Job duties:
•
•
•
Director of information technology for the College of Science.
Supervise, maintain and administer the information technology infrastructure of the Dept. of Statistics at Texas A&M
University.
Supervisor of two “Senior Microcomputer/LAN Administrators” in the Dept. of Statistics.
Service:
•
Information Technology Advisory Committee (2008-Pres.) University wide committee to advise Texas A&M on IT
matters.
•
Information Policy Committee (2008-Pres.). University wide committee to propose and review Texas A&M IT policy.
•
Member of the Brazos Architecture and Oversight Committee. Brazos is a 300 node HPC cluster.
Course Taught:
•
Engineering Statistics (STAT 2011). 1996-2007.
•
Advanced Topics in Computational Statistics (STAT 605).
1
269
SIMON SHEATHER
Education:
University of Melbourne
La Trobe University
Appointments:
Professor
Professor
Associate Professor
Lecturer / Senior Lecturer
Professor (Visiting)
Associate Professor (Visiting)
Statistics
Statistics
B.S. 1st class honors (1981)
Ph.D. (1986)
Department of Statistics, Texas A& M University
AGSM, University of NSW
AGSM, University of NSW
AGSM, University of NSW
Stern School of Business, NYU
Department of Statistics, Penn State
2005-Present
1998-2005
1994-1997
1987-1993
2001
1987
Publications:
i. Last five years (10 selected from a total of 17):
1. Savchuk, O., Hart, J., & Sheather, S.J. (2010). Indirect cross-validation for density estimation. Journal of the
American Statistical Association, 489, 415-423.
2. Lindsey, C., & Sheather, S. (2010). Power transformation via multivariate Box–Cox. Stata Journal, 10, 69-81.
3. Phisitkul1, S., Khanna, A., Simoni, J., Broglio, K.R., Sheather, S.J., Rajab, M.H. & Wesson, D.E. (2010).
Amelioration of metabolic acidosis in patients with low GFR reduced kidney endothelin production and kidney
injury, and better preserved GFR. Kidney International, 77, 617–623.
4. Mahajan, A., Simoni, J., Sheather, S.J., Broglio, K.R., Rajab, M.H. & Wesson, D.E. (2010). Daily oral sodium
bicarbonate preserves glomerular filtration rate by slowing its decline in early hypertensive nephropathy. Kidney
International, 78, 303-309.
5. Wesson, D.E., Simoni, J., Broglio, K.R. & Sheather, S.J., (2011). Acid retention accompanies reduced GFR in
humans and increases plasma levels of endothelin and aldosterone. American Journal of Physiology – Renal
Physiology, 300, 830-837.
6. Sheather, S.J. & South, J. (2012). Texas A&M Department of Statistics, Strength in Numbers: The Rising of
Academic Statistics Departments in the U.S., Agresti and X.-L. Meng (eds.), Springer, New York, 301-316.
7. Prendergast, L. and Sheather, S.J. (2013). On sensitivity of inverse response plot estimation and the benefits of a
robust estimation approach. Scandinavian Journal of Statistics, 40, 219-237.
8. Savchuk, O., Hart, J., & Sheather, S.J. (2013). One-sided cross-validation for non-smooth regression functions.
Journal of Nonparametric Statistics, 25, 889-904.
9. Lindsey, C., Sheather, S.J. & McKean, J.W. (2014). Using Sliced Mean Variance-Covariance Inverse Regression
for classification and dimension reduction. Computational Statistics, 29, 769-798.
10. Lindsey, C.D. and Sheather, S.J. (2014). Building valid regression models for biological data. Biological
Knowledge Discovery Handbook. Wiley, New York, 441-476.
ii. Other Noteworthy Publications:
1. Staudte, R.G. & Sheather, S.J. (1990). Robust Estimation and Testing. Wiley, New York.
2. Sheather, S.J. & Jones, M.C. (1991). A reliable data-based bandwidth selection method for kernel density
estimation. Journal of the Royal Statistical Society, Series B, 53, 683–690.
3. Hettmansperger, T.P. & Sheather S.J. (1992). A cautionary note on the method of least median squares. American
Statistician, 46, 79-83.
4. Ruppert, D., Sheather, S.J. & Wand, M.P. (1995). An effective bandwidth selector for local least squares
regression. Journal of the American Statistical Association, 90, 1257-1270.
5. Barnett, G., Kohn, R. & Sheather, S. (1996). Robust estimation of an autoregressive model using Markov chain
Monte Carlo. Journal of Econometrics, 74, 237-254.
6. Hettmansperger, T.P., McKean, J.W., and Sheather, S.J. (2000). Robust nonparametric methods. Journal of the
American Statistical Association, 95, 1308-1311.
7. Sheather, S.J. (2004). Density estimation, Statistical Science, 19, 588-597.
1
270
8.
*Spiegelman, C., Tobin, W. A., James, Sheather, S.J., Wexler, S.& Roundhill, D. M. (2007). Chemical and
forensic analysis of JFK assassination bullet lots: Is a second shooter possible? Annals of Applied Statistics, 1,
287–301.
9. Lauziere, I., Sheather, S. and Mitchell, F. (2008). Seasonal abundance and spatio-temporal distribution of
dominant xylem fluid-feeding Hemiptera in vineyards of Central Texas and surrounding habitats. Environmental
Entomology, 37, 925-937.
10. Sheather, S. J. (2009). A Modern Approach to Regression with R. Springer, New York.
Grants in last five years:
1. NIH, $100,000, “Lipoprotein Density Profiling for Clinical Studies”, 2008-2011.
2. NSF, $300,000, “Texas Census Data Research Center”, 2011-2014.
3. SAS, $1,000,000, “Development of a new MS (Analytics) degree program”, 2013-2014.
Awards and Honors:
1. Australian Graduate School of Management (AGSM) Alumni Association Award for Excellence in Teaching (1991,
1997, 2000)
2. University of New South Wales Vice Chancellor’s Award for Teaching Excellence (1994)
3. Fellow of the American Statistical Association (2001)
4. Listed on ISIHighlyCited.com among the top one-half of one percent of all mathematical scientists, in terms of
citations (2001-2013). According to Google scholar, 7827 citations as of 3/8/15 (including 697 in 2014).
5. Inaugural AGSM Award for Excellence in Research (2002)
6. American Statistical Association, Statistics in Chemistry Award (2008) (based on publication * above)
7. Fish Camp Namesake, Texas A&M University (2012)
8. Mentor of the winning student teams in the 2012 & 2014 Capital One National Statistical Modeling Competitions
9. Texas A&M University Association of Former Students Distinguished Achievement College-Level Teaching Award
(2013)
Service: (last 5 years)
Major Administrative Roles:
1. Head of the Department of Statistics (2005-2014)
2. Director of Online Programs, Department of Statistics (2011 – present)
3. Academic Director of MS Analytics Program, Department of Statistics (2013- present)
4. President, Texas A&M Statistical Services, LP (2012 – present)
Selected National/International Service:
1. Chair of the External Review Committee for the Department of Statistics at the University of Kentucky (2012)
2. External Review Committee for the Department of Mathematics and Statistics at the University of Cyprus (2012)
3. External Review Committee for the Department of Statistics at the University of British Columbia (2013)
University committees:
1. Chair, Faculty Evaluation Task Force on Teaching, President’s Task Force on Faculty Evaluations (2009-2010)
2. Massive Open Online Course (MOOC) Exploration Committee (2012-2013)
3. Core Curriculum Technology Enhanced Grant Committee (2012-2015
4. Activity leader for the ADVANCE leadership development program for Department Heads (2012-2014)
5. Member (2011-2013) and Chair of the Department Head Council (2013-2014)
6. Member of the President’s Council on Climate and Diversity (2013-2014)
7. Email Selection Advisory Committee (2013-2014)
8. Massive Open Online Course (MOOC) Advisory Committee (2013-2014
9. Strategic Re-allocation Sub-Council (2013-2014)
10. Price Waterhouse Coopers Advisory Committee (2013-2014)
2
271
11. College of Science Selection Committee for The Association of Former Students' College-Level Teaching Awards
(2014)
12. Search Advisory Committee for the Dean of Science (2014-2015)
Community Service:
1. Member of the Board of the Boys and Girls Club of the Brazos Valley (2011 - present)
Students Supervised (last 5 years):
Ph D – 4 students
1. Olga Savchuk (2009), Choosing a Good Kernel for Cross-Validation (co-chair with J. Hart)
2. Charles Lindsey (2010), SMVCIR Dimensionality Test (chair)
3. Bradley Barney (2011), Bayesian Joint Modelling of Binomial and Rank Response Data (co-chair with V. Johnson)
4. Dominic Jann (2012), Bayesian Methods for Record Matching (co-chair with M. Speed)
MS (Statistics) – 50 students
1. Clarissa La (2010), Retaining Loyal, High-Value Hilton Honors Members (co-chair with M. Speed)
2. Shira Hetz (2011), Comparison of Bandwidth Selectors for Kernel Density Estimates (chair)
3. Jack Bennett (2012), Play Testing Games using Statistical Methods (chair)
4. Stephanie Platt (2013), Red, red wine: Model selection using Portuguese wine (chair)
5. Kathleen Hosek (2014), Modeling residence hall utilities consumption (chair)
6. Lisa Szydziak (2014), Data.Medicare.gov – Statistical modeling of Hospital Compare data (chair)
7. Taylor Davis (2014), Predicting changes in customer satisfaction (chair)
8. Alex Bessinger, Joel Galang, Joseph Magagnoli, Jennifer Morse and Hung Tran (2014), A model for opening
weekend box office revenue based on Wikipedia activity (co-chair with A. Dabney)
9. Daniel Evert, Michael Knous, Christopher Rodriguez and Samuel Temple (2014), Logistic regression models for
predicting the probability of a birdie or better on the PGA tour (co-chair with A. Dabney)
10. Daniel Byler, Jonathan Goodhue, Warren Roane and Kelvin Li (2014), A model for predicting price of Toyota
certified preowned Camry vehicles (co-chair with M. Katzfuss)
11. Dan Liu, Alex Pestrikov, Richard Chapman, Lance Costello and Uday Hejmadi (2014), Predicting daily usage in the
Capital Bikeshare system (chair)
12. Sydney Anuskiewicz, Patrick Clark, Thomas Duffy, Andrea Ferris, Raymond Kui, Alana Moczydlowski, Wenxin
Pang, Johannes Roijen, Eric Talarico and Sui Zhang (2015), Predicting credit events in 30 year mortgages using the
Freddie Mac loan performance data (chair)
13. Teresa Barnett, Nicholas Darschewski, Jin Do, Jeremy Fergason, Jonathan Presto and Daniela Sakamoto (2015),
Predicting US gross movie box office receipts along with days in release (chair)
14. Lynetta Campbell, Felipe Chacon, John Czarnek, Jeffrey Kirk and Susan Uland (2015), Predicting sound pressure
levels using a data set from NASA (chair)
15. Garrett Anderson, Wenhoung Fan, Paul Garrett and Shuhua Xia (2015), Predicting daily utility consumption in
residence halls at TAMU (chair)
MS (Analytics) – 8 students
1. Steve Bowden (2015), Predicting churn (chair)
2. Aaron Agnew (2015), Modeling credit events (chair)
3. Lauren Engle (2015), Modeling loyalty program usage (chair)
4. Danny Leonard (2015), Modeling the effect of price on demand (chair)
5. Erin Parrott (2015), Predicting future demand (chair)
6. Mike Bergeron (2015), A pricing model (co-chair with E. Jones)
7. Bora Tarhan (2015), Modeling gasoline prices across the US (co-chair with M. Speed)
8. Salsawit Shifarraw (2015), Modeling in-patient ratings of hospital care (co-chair with E, Jones)
3
272
MICHAEL SHERMAN
Education:
Department of Mathematics, University of Massachusetts, Amherst
Department of Statistics, University of North Carolina at Chapel Hill
Department of Statistics, University of North Carolina at Chapel Hill
Mathematics
Statistics
Statistics
B.A. (1987)
M.S. (1990)
Ph.D. (1992)
Appointments:
Professor
Associate Professor
Assistant Professor
Postdoctoral Fellow
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
Department of Biostatistics, University of Rochester
2008–present
1999–2008
1994–1999
1992–1994
Publications:
i. Last five years:
1. (with K. Lennox) Efficient experimental design for binary matched pairs data, Statistics in Medicine, (2009),
28, 2952–2966.
2. (with Y. Parmet and E. Schechtman) Factor analysis revisited: how many factors are there?, Communications
in Statistics, (2010), 39, 1893–1908.
3. (with K. Baum et al.) Spatial distribution of Africanized honey bees in an urban landscape, Urban Landscape
and Planning, (2011), 100, 153-162.
4. Spatial Statistics and Spatio-Temporal Data: Covariance Functions and Directional Properties, (2011), John
Wiley & Sons, Ltd., Chichester, UK.
5. (with A. Maity and S. Wang) Inferences for the ratio: Fiellers interval, log ratio, and large sample based
confidence intervals, Advances in Statistical Analysis, (2011).
6. (with A. Maity) Testing for spatial isotropy under general designs, Journal of Statistical Planning and Inferences, (2012), 42, 1081–1091.
7. (with J. Lim et al.) Parameter estimation in the spatial auto-logistic model with varying independent subblocks,
Computational Statistics and Data Analysis, (2012) 56, 4421–4432.
8. (with J. Lim et al.) A 2-dimensional fused lasso, Journal of Multivariate Analysis, (2015) under review.
ii. Other Noteworthy Publications:
1. Sherman, M., and Carlstein, E. (1996). Replicate histograms. Journal of the American Statistical Association,
91, 566–576.
2. Sun, Y., and Sherman, M. (1996). Some permutation tests for survival data, Biometrics, 52, 87–97.
3. Sherman, M. (1996). Variance estimation for statistics computed from spatial lattice data, Journal of the Royal
Statistical Society, Series B, 58, 509–523.
4. Sherman, M. (1997). Subseries methods in regression, Journal of the American Statistical Association, 92,
1041–1048.
5. Politis, D., and Sherman, M. (2001). Moment estimation for statistics from marked point processes, Journal
of the Royal Statistical Society, Series B, 63, 261–275.
6. Guan, Y., Sherman, M., and J.A. Calvin (2004). A Nonparametric test for isotropy using subsampling, Journal
of the American Statistical Association, 99, 810–821.
1
273
7. Guan, Y., Sherman, M. (2007). On least squares fitting for stationary spatial point processes, Journal of the
Royal Statistical Society, Series B, 69, 31–49.
8. Li, B., Genton, M., and Sherman, M. (2007). A Nonparametric assessment of properties of space-time covariance functions, Journal of the American Statistical Association, 102, 736–744.
9. Li, B., Genton, M., and Sherman, M. (2008). Testing the covariance structure of multivariate random fields
Biometrika, 95, 813–829.
Grants in last five years:
i. Last five years:
1. National Institute of Health R01 Award, “Fetal Alcohol Exposure and Neurodevelopment”, AA-13440-04,
Collaborator, Rajesh Miranda P.I., 2002–2012.
ii. Other Noteworthy Grants:
1. National Institute of Health R01 Award, “Risk of Childhood Cancers Associated with Agricultural Use”, CA92670, Co-PI, 2001-2008.
2. 1996–2002 National Institute of Health FIRST Award, “Subsampling Methods for Spatial and Longitudinal
Data”, CA-72015. P.I. 1996-2002.
Awards and Honors:
1. Elected member of the International Statistical Institute (ISI),
2. College of Science Distinguished Achievement Award from the Association of Former Students at Texas A&M
University, 2002
3. Member of Editorial Boards:
Journal of the American Statistical Assoc. (JASA) (2005-2014).
Biometrics (1998-2000).
Service:
Member of Site Visit Team for the Carolina Population Center, March 2000.
Refereed Papers (Proposals) for:
Annals of the Institute of Statistical Mathematics, Annals of Statistics, Biometrics, Biometrical Journal, Communications
in Statistics, Environmental and Ecological Statistics, Journal of the American Statistical Association, Journal of Computational Statistics and Data Analysis, Journal of Pediatric Oncology, Journal of the Royal Statistical Society, Journal of
Statistical Planning and Inference, Mathematical Methods of Statistics, National Science Foundation, National Security
Agency, Simulation, South African Research Foundation, State of Louisiana, Statistica Neerlandica, Statistics and Probability Letters.
Students Supervised:
Ph.D. Students mentored at Texas A&M:
Yongtao Guan (advised jointly with J.A. Calvin)
Eric Hintze
Bo Li (advising jointly with R.J. Carroll)
Elizabeth Young
Master’s Students mentored at Texas A&M:
Susan Gao
Xiaoqi Li
2
274
Min Chen
Justin Chown
Lei Wang
Todd Napier
Celeste Wilson
Stephanie Berland
Served on Master’s or Ph.D. Students mentored at Texas A&M 2006-present:
Shuo Feng
Negin Alemazkoor
Nishal Kafle
Zachary Scott
Melissa Lee
Jincheol Park
Jason Poole
Hisham Almohammadi
Angela Brown
Soutir Bandyopadhyay
Eric Talbot
Dlonglin Han
Xiaso Zeng
Ying Sun
Roma Garg
Yanru Zhang
Siqi Li
3
275
SAMIRAN SINHA
Education:
Kalyani University, West-Bengal, India
Calcutta University, West-Bengal, India
University of Florida, Florida, USA
Appointments:
Visiting Associate Professor
Associate Professor
Visiting Assistant Professor
Assistant Professor
Statistics
Statistics
Statistics
B.Sc. (1997)
M.Sc. (1999)
Ph.D. (2004)
Michigan State University
Texas A&M University
Michigan State University
Texas A&M University
2011
2010–present
2009-2010
2004-2010
Publications:
i. Last five years (max 10):
1. Sinha, S. and Ma, Y. (2014). Semiparametric analysis of linear transformation models with covariate measurement errors. Biometrics, 70, 21–32.
2. Sinha, S., Saha, K. K., and Wang, S. (2014). Semiparametric approach for non-monotone missing covariates
in a parametric regression model. Biometrics, 70, 299–311.
3. Maiti, T., Ren, H. and Sinha, S. (2014). Prediction error of small area predictors with shrinking both mean
and variances. Scandinavian Journal of Statistics, 41, 775–790.
4. Sinha, S. and Yoo, S. (2013). Score tests in the presence of errors in covariate in matched case-control studies.
Journal of Multivariate Analysis, 115, 157–171.
5. Sinha, S. (2012). A functional method for conditional logistic regression with errors-in-covariates. Journal
of Nonparametric Statistics, 24, 577–595.
6. Sinha, S., Mallick, B. K., Kipnis, V., and Carroll, R. J. (2010). Semiparametric Bayesian analysis of nutritional
epidemiology data in the presence of measurement error, Biometrics, 66, 444–454.
7. Chatterjee, N., Sinha, S., Diver, W. R., and Feigelson, H. S. (2010). Analysis of cohort studies with multivariate, partially observed, disease classification data, Biometrika, 97, 683–698.
8. Sun, J. X., Sinha, S., Wang, S., and Maiti, T. (2010). Bias reduction in conditional logistic regression.
Statistics in Medicine, 30, 348–355.
9. Sinha, S. (2010). An estimated-score approach for dealing with missing covariate data in matched case-control
studies, The Canadian Journal of Statistics, 38, 680–697.
10. Ahn, J., Mukherjee, B., Gruber, S. B., and Sinha, S. (2010). Missing exposure data in stereotype regression
model: application to matched case-control study with disease subclassification, Biometrics, 67, 546–558.
ii. Other Noteworthy Publications:
1. Dass, S. C., Maiti, T., Ren, H. and Sinha, S. (2012). Confidence interval estimation of small area parameters
shrinking both mean and variances. Survey Methodology, 38, 173–187.
2. Sinha, S. and Wang, S. (2009). A new semiparametric procedure for matched case-control studies with
missing covariates, Journal of Nonparametric Statistics, 21, 889–905 .
3. Sinha, S. and Maiti, T. (2008), Analysis of matched case-control data in presence of nonignorable missing
data, Biometrics, 64, 106–114.
1
276
4. Sinha, S., Gruber, S. B., Mukherjee, B., and Rennert, G. (2008), Inference of haplotype effect in matched
case-control study using unphased genotype data, International Journal of Biostatistics, 4, Issue 1, Article 6.
5. Sinha, S., Mukherjee, B., and Ghosh, M. (2007), Modelling association among multivariate exposures in
case-control studies, Sankhya, 69, 379–404.
6. Mukherjee, B., Zhang, L., Ghosh, M., and Sinha, S. (2007), Semiparameteric Bayesian analysis of casecontrol data under gene-environment independence and population stratification, Biometrics, 63, 834–844.
7. Mukherjee, B., Liu, I., and Sinha, S. (2007), Analyzing matched case-control data with multiple ordered
disease states, possible choices, and comparisons, Statistics in Medicine, 26, 3240–3257.
8. Sinha, S., and Mukherjee, B. (2006), A score test for determining sample size in matched case-control studies
with categorical exposure, Biometrical Journal, 48, 35–53.
9. Sinha, S., Mukherjee, B., Ghosh, M., Mallick, B. K., Carroll, R. J. (2005), Semiparametric Bayesian Analysis
of Matched case-control studies with missing exposure, Journal of the American Statistical Association, 100,
591–601.
10. Sinha, S., Mukherjee, B., and Ghosh, M. (2004), Bayesian semiparametric modeling for matched case-control
studies with multiple disease states, Biometrics, 60, 41–49.
Grants in last five years:
i. Last five years:
1. National Institute of Health, $150,000, “Innovative approaches for analyzing SEER breast cancer data”, 20132015.
2. National Science Foundation, $44,500, “Statistical Methods based on parametric and semiparametric hierarchical models to solve problems related to socio-economic-demographic deprivation measure”, 2010-2013.
3. National Science Foundation, $26,858, “The 13th New Researcher Conference in Statistics and Probability”,
2010.
4. National Institute of Health, $20,000, “The 13th New Researcher Conference in Statistics and Probability”,
2010.
5. National Security Agency, $12,700, “The 13th New Researcher Conference in Statistics and Probability”,
2010.
Service:
Sessions organized in conferences in the last 5 years:
1. Organizer of one invited session in the IISA 2014. Title of the session: “Inverse problems with application in
statistics”. Speakers: Xiaofeng Wang, Jean-Pierre Florens, and Samiran Sinha.
2. Chaired the session “Bayes estimation in Modern Cancer Epidemiological Studies” in the IISA 2014, Riverside,
CA.
3. Organized one invited session in the ENAR meeting 2011. Title of the session: ”Disease mapping and spatial
regression as emerging tools for surveillance epidemiology”. Speakers: Peter Congdon, Lance Waller, Tapabrata
Maiti, and Andrew Lawson.
4. Chaired the session ”Disease mapping and spatial regression as emerging tools for surveillance epidemiology” in
the ENAR 2011 meeting.
5. Chair of the IMS new researchers conference organizing committee for the year of 2010 which was held in Vancouver, Canada. The details of the conference can be found at
http://www.stat.tamu.edu/˜sinha/nrc2010-ims.html.
2
277
6. Organizer of one invited session in the ENAR meeting 2010. Title of the session: “Shrinkage estimation in Microarray data analysis”. Speakers: James Booth, Marina Vannucci, Dan Nettleton, and Tapabrata Maiti.
7. Organizer of one invited session in the Biometrics Section for the 2009 Joint Statistical Meeting (JSM). Title of the
session: The issue of high dimensionality and missing data in complex epidemiological studies. Speakers: Rebecca
Betensky, Nicholas P. Jewell, Bin Nan, and John Neuhaus. Discussant: Samiran Sinha.
Students Supervised:
Ph.D students:
Jiangang Miao (2014); Dissertation was on missing data and measurement errors in epidemiological studies.
Jenny X. Sun (2010); Dissertation was on small sample bias corrections in the conditional logistic regression.
Master’s students:
Seungyoon Yoo (2010)
Minkyung Oh (2011)
Charles Gordon (2012)
Jenn Hanley-Burkhart (2012)
Stacie Blaskowski (2012)
Abigail Green (2013)
Craig Kreisler (2013)
3
278
CLIFFORD H. SPIEGELMAN
Education:
SUNY at Buffalo
Northwestern University
Northwestern University
Statistics/Mathematics/Economics
Managerial Economics
Applied Math/Statistics
Appointments:
Distinguished Professor
Professor
Senior Research Scientist
Department of Statistics, Texas A& M University
Department of Statistics, Texas A& M University
Texas A&M Transportation Institute (TTI)
B.S (1970)
M.S. (1973)
Ph.D. (1976)
2009-Pres.
1990-2008
2004-Pres.
Selected Publications out of 13:
i. Last five years:
1. Nagyvary, Joseph, Guillemette, Ray, and Spiegelman, Clifford (2009). “Mineral Preservatives in the Wood of
Stradivari and Guarneri”, PLoS ONE, http://dx.plos.org/10.1371/journal.pone.0004245 (see awards and honors
section for coverage of this paper)
2. Paulovich, … Spiegelman, C., Stein, S., Tempst, P., Liebler, D. (2009). “A CPTAC Inter-laboratory Study
Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance”,
http://www.mcponline.org/cgi/reprint/M900222-MCP200v1
3. Rudnick, … Spiegelman, C., Tempst, P., Liebler, D., and Stein, S. (2009). “Performance Metrics for Liquid
Chromatography-Tandem Mass Spectrometry Systems in Proteomic Analyses and Evaluation by the CPTAC
Network”, MCP Papers in Press, http://www.mcponline.org/cgi/reprint/M900223-MCP200v2
4. Addona, T., … Spiegelman, … Carr, S. (2009). “Multi-site assessment of the precision and reproducibility of
multiple reaction monitoring–based measurements of proteins in plasma”, Nature Biotechnology, 27, 633 – 641.
5. Tabb, D., … Spiegelman, C.H. (Communicating Author) “Repeatability and Reproducibility in Proteomic
Identifications by Liquid Chromatography- Tandem Mass Spectrometry”. Journal of Proteome Research,9, 761776
6. Nell Sedransk, … Cliff Spiegelman “Make Research Data Public?-Not Always so Simple”: A Dialogue for
Statisticians and Science Editors; Statist. Volume 25, Number 1 (2010), 41-50.
7. Rudnick, P.A., …Spiegelman, C., Tempst, P., Liebler, D.C., Stein, S.E., Performance Metrics for Liquid
Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses, Mol. Cell Proteomics, 2010 Feb.,
9(2), pp. 225-241.
8. Tarone, A. M.; Picard, C. J.; Spiegelman, C.; et al. (2011). Population and Temperature Effects on Lucilia sericata
(Diptera: Calliphoridae) Body Size and Minimum Development Time. Journal Of Medical Entomology (48)
5,1062-1068, DOI: 10.1603/ME11004
9. A Nonparametric Approach Based on a Markov like Property for Classification- Review Article Chemometrics
and Intelligent Laboratory Systems, Volume 108, Issue 2, 15 October 2011, Pages 87-92 Eun Sug Park, Clifford
Spiegelman, Jeongyuon Ahn
10. Lahiri, S. N., Spiegelman, C., Appiah, J., and Rilett. L. Gap Bootstrap Methods for Massive Data Sets With An
Application To Transportation Engineering. The Annals of Applied Statistics Vol. 6, No. 4, 1552–1587.
11. Spiegelman C, and Tobin W A. Analysis of experiments in forensic firearms/toolmarks practice offered as support
for low rates of practice error and claims of inferential certainty. Law, Probability and Risk; 12:115-133.
12. Park E.S., Hopke P. K., Oh M. S., Symanski E., Han D., Spiegelman C. H. Assessment of source-specific health
effects associated with an unknown number of major sources of multiple air pollutants: a unified Bayesian
approach., Biostatistics 15, 3, 484 -497.
13. Owings Charity G., Spiegelman Cliff, Tarone Aaron M. and Tomberlin Jeffery K., Developmental variation
among Cochliomyia macellaria Fabricius (Diptera: Calliphoridae) populations from three ecoregions of Texas,
USA, Int J Legal Med, DOI 10.1007/s00414-014-1014-0.
ii. Other selected Noteworthy Publications:
1. Spiegelman, C., Tobin, W.A., James, W.D., Sheather, S., Wexler, S., & Roundhill, D.M. (2007). Chemical and
Forensic Analysis of JFK Assassination Bullet Lots: Is a Second Shooter Possible, Annals of Applied Statistics.
(1)2, 287-301. Feature on national and international television, and print media on all continents, see the honors
and awards section.
1
279
Grants/Cooperative Agreements in last five years. Spiegelman as PI:
i. Last five years:
1. (NASS/USDA), $ 419,306, Census Calibration Weighting, 2014-2017
2. TAMU/Weizmann, $88,000 A non-parametric Markov approach to classification and regression, 2012-2015
3. Southwestern University Transportation Research Center (SWUTC/USDOT), $135,253, “Write a transportation
textbook and associated course creation, 2008-2014
ii.
Southwestern University Transportation Research Center (SWUTC/USDOT), How do Travelers Perceive the
Value of Travel Time Reliability? $45,000. (Joint PIs Burris from TAMU Civil Engineering and Spiegelman)
2013-2014.
iii.
Grants where Spiegelman was Co-PI, Heath Effects Institute, $251,814 (through TTI) Development of enhanced
statistical methods for assessing health effects associated with an unknown number of major sources of multiple
air pollutants 2009-2014.
iv. Other Noteworthy Grants/Cooperative Agreements:
1. NCI 2006-2009, SAIC-Frederick-NCI-Proteomic Technology”, $2,170,547 for helping run the NCI proteomics
program, particularly the statistical aspects.
Awards and Honors:
i. NRC noteworthy awards:
1. 2002 and 2008- Statistics in Chemistry Awards for Best Paper by the ASA
2. 1991- W. J. Youden Award given by the American Statistical Association for the best paper on Interlaboratory
Comparisons
3. 2015-2016 Co-chair SAMSI program on forensic science.
4. 2012-Present. Member of 9 person Technical Advisory Board for the Houston Forensic Science LGC (The city of
Houston crime lab.)
5. 2014-Fellow of the American Association for the Advancement of Science (AAAS),
6. 2013-Honor University wide lecture on the forensic aspects of the JFK assassination 50-year anniversary lecture.
All of the networks ABC, NBC, and CBS covered the talk. The work was also cited extensively in
7. 2012-2013 Invited to write a series of editorials for the Austin American Statesman on the state of forensic science
in this country. Three were written and featured on the first page of the editorial section and 2 were above the fold.
8. 2009- Paper with Nagyvary covered by international print media including Time Magazine and the Christian
Science Monitor
9. 2008-2014-National Institute of Statistical Sciences (NISS) Board of Directors (term limited off), and Department
representative 2004-present.
10. 2007- Jerome Sacks Award for Cross-Disciplinary Research. This award is given to an individual whose work is
cross-disciplinary and encompasses innovation in the statistical sciences. Preference will be given to work that
creates new research relationships or substantially buttresses extant relationships.
11. 2007- Honor- Interviewed by NBC Nightly News, CNN Situation Room, Geraldo at Large, The Washington Post,
and may other national radio and newspapers about the JFK paper. It was a worldwide story and the lead story on
Fox News for 2 days.
12. 1994-Distinguished Achievement Award, ASA Section on the Environment
13. 1993-Elected member of the International Statistical Institute (ISI)
14. 1992-Fellow of the American Statistical Association (ASA),
15. 1990-Fellow of the Institute of Mathematical Statistics (IMS)
16. 1985-Presant. 30 year long coeditor (founding) Chemometrics and Intelligent Laboratory Systems
17. Various editorial boards including JASA (one moth as acting T&M editor), Environmetrics, J. Chemometrics, J. of
Proteomics (an ACS journal), Journal of Transportation Statistics and its successor The Journal of Transportation
and Statistics.
Service:
ii. Sessions Organized and Work at National and International Meetings:
1. Co-organizer of 3 International Chemometrics Meetings (1985 in Gaithersburg NBS (now called NIST) 1991 at
TAMU, 1995 and 2000 in Las Vegas)
2
280
2.
3.
4.
5.
6.
7.
8.
1987 - 1991 Head ASA Committee on Statistics in Chemistry.
2002-2003 Head and Co-organizer of Transportation Interest Group with the ASA Editorial.
2003-2004 NRC committee for the FBI Bullet Lead Analysis.
2002-2012 Member, Committee on Statistical Methodology and Statistical Computer Software in Transportation
Research, Transportation Research Board, Division of NRC. I was term limited off.
Numerous JSM-ASA sessions on Forensic Science, Transportation, Environmetrics, and Chemometrics. I did not
keep records, but they should be available from JSM programs. Also, I organized at least 2 Transportation
Research Board (TRB) sessions and in 2012 with Larry Rilett gave a full day short course on micro simulation at
the Transportation Research Board. (It should be apparent that I organize meetings and sessions for effect and
not vita entries.)
AAAS Annual meeting 2013 session on Forensics Science
AAAS Annual meeting 2014 session on Data Availability (a featured session selected for web broadcasting
around the world.)
Students Supervised:
Ph.D. Students Chaired:
1991 Chyon-Hwa Yeh
1997 Eun Sug Park
2000 Byron Gajewski
2001 Jacqueline Kiffe (Co-Chair)
2002 Naijun Sha (Co-Chair)
2012- Mary Frances Dorn
MS Students (During the last 4 years):
Lacy Brown - PhD in CVEN
Zehra Yalcin - MS in BAEN
Xiduo Wang - MS in CVEN
Robert E. Saw (current) - MS in STAT
Raymond Kui - MS in STAT
Chong Chin Heo - PhD in ENTO
Melissa Lee (Chair) - MS in STAT
Santosh Rao R. Danda (Did extensive work with him and on the supporting grant)- MS in CVEN
Liteng, Zha - MS in CVEN
Ryan Brady (Chair) - MS in STAT
Nicholas Nimchuk (Chair) - MS in STAT
Ernesto Ramos (Doing extensive work with him and expect a joint paper) - MS in ENTO
Zhi Chen - MS in CVEN
Tao Zhang - MS in CVEN
Nathan Shetty (joint chair) - MS in STAT
Bo Wang - MS in CVEN
Yiyi Wang (worked a lot with him) - PhD in STAT
Siamak Saliminejad - PhD in CVEN
Shuo Feng - PhD in STAT
Brian Shollar - MS in CVEN
Gregory Joseph Cepluch- MS in STAT
Benjamin Robert Sperry (Worked extensively with him) - PhD in CVEN
Nathaniel Allen Joy – (worked extensively with him) MS in AGEC
Jinpeng Lv - PhD in CVEN
Mehdi Azimi - PhD in CVEN
3
281
SUHASINI SUBBA RAO
Education:
University of Bristol
Mathematics
Appointments:
Associate Professor
Assistant Professor
Lecturer
Postdoctoral Fellow,
Texas A&M, USA
Texas A&M, USA
University of Bristol, UK
Universit¨at Heidelberg, Germany
Ph.D. (2001)
2010-present
2006-2010
2005-2006
2001-2005
Publications:
i. Last five years:
1. A test for stationarity of a Multivariate time series (Carsten Jentsch and Suhasini Subba Rao) (2015) Journal
of Econometrics, 185, pages 124–161.
2. BaSTA: consistent multiscale multiple change-point detection for piecewise-stationary. (Piotr Fryzlewicz and
Suhasini Subba Rao) (2014) JRSS(B), 76, pages 903–924.
3. The Handbook of Statistics, vol 30 (Time Series Analysis: Methods and Applications) (co-Editor) (2012).
4. Statistical inference for Stochastic Coefficient Regression models (2012). Handbook of Statistics, vol 30.
5. A test for second order stationarity of a time series based on the Discrete Fourier Transform (Yogesh Dwivedi
and Suhasini Subba Rao) (2011) Journal of Time Series Analysis, 32, pages 68–91.
6. On mixing properties of ARCH and time-varying ARCH processes, (Piotr Fryzlewicz and Suhasini Subba
Rao) (2011) Bernoulli.
7. Nonparametric estimation for dependent data (Jan Johannes and Suhasini Subba Rao), (2010), Journal of
Nonparametric Statistics, 23, pages 661–681.
ii. Before 2010:
1. Statistical analysis of a spatio-temporal model with location dependent parameters and a test for spatial stationarity. (Suhasini Subba Rao) (2008), Journal of Time Series Analysis (29) pages 673–694.
2. Normalised least squares estimation for time-varying ARCH processes. (Piotr Fryzlewicz, Theofanis Sapatinas and Suhasini Subba Rao), (2008), Annals of Statistics, 36, pages 742–786.
3. Statistical analysis of time series models for minimum/maximum temperatures in the Antarctic Peninsula
(Gillian Hughes, Suhasini Subba Rao and Tata Subba Rao), (2007) Proceedings of the Royal Society (A), 463,
pages 241–259
4. A recursive online algorithm for the estimation of time-varying ARCH parameters. (Rainer Dahlhaus and
Suhasini Subba Rao), (2007), Bernoulli, 13, pages 389–422.
5. On some nonstationary, nonlinear random processes and their stationary approximations. (Suhasini Subba
Rao) (2007), Advances in Applied Probability 38, pages 1155-1172.
6. A Haar-Fisz technique for locally stationary volatility estimation. (Piotr Fryzlewicz, Theofanis Sapatinas and
Suhasini Subba Rao), (2006), Biometrika 93, pages 687-704.
7. A note on uniform convergence of an ARCH(∞) estimator. (Suhasini Subba Rao) (2006) Sankhya, 68, pages
600–620.
1
282
8. Statistical inference of time-varying ARCH processes (Rainer Dahlhaus and Suhasini Subba Rao), (2006),
Annals of Statistics 34, pages 1074-1114.
9. On multiple regression models with nonstationary correlated errors. (Suhasini Subba Rao) (2004) Biometrika
91, pages 645-659.
Grants and visits in the past 5 years:
i. Grants:
1. NSF: P.I. for grant titled: Fourier based methods for analysing nonstationary and nonlinear time series [20112014].
2. NSF: P.I. for grant titled: Beyond Stationarity: Statistical inference for nonstationary processes [2008-2011].
ii. Academic visits: Universit¨at Heidelberg, June 2010 and November, 2011, Institute of Mathematical Science, Singapore, June 2012, Isaac Newton Institute, Cambridge, January 2014.
Service:
1. Member of Editorial Board: Statistics (2012-Present).
2. Proposal Reviewer: NSF (2008), FONDECYT - Chile Research Foundation (2010), NSA (2012), NSA (2013).
3. Proposal Panelist: NSF Statistics (Jan, 2010), NSF FRG (Nov, 2012).
PhD Students Supervised and committee:
1. Advised: Jun Bum Lee (2012)
2. Committee: Lianfu Chen (2011), Priya Kohli (2012). Others whose name I cannot remember.
2
283
SUOJIN WANG
Education:
Zhejiang University
University of Texas at Austin
Appointments:
Professor
Joint Professor
Visiting Professor
Visiting Professor
Visiting Professor
Visiting Professor
Associate Professor
Senior Research Fellow
Assistant Professor
Research Associate
Mathematics
Statistics
B.S. (1982)
Ph.D. (1988)
Department of Statistics, Texas A&M University
Department of Epidemiology and Biostatistics,
Texas A&M University Health Science Center
Australian National University; University of
Wollongong; Monash University
King Abdullah University of Science and
Technology
University of Wollongong; Australian National
University
University of Southampton; Swiss Federal
Institute of Technology; University of Geneva
Department of Statistics, Texas A&M University
Survey Methods Research, Bureau of Labor
Statistics, Washington, D.C.
Department of Statistics, Texas A&M University
Department of Statistical Science,
Southern Methodist University
1998–present
1998–present
Fall 2013
Fall 2011
Fall 2010, Fall 2006
1999
1993–1998
1994
1990–1993
1988–1990
Selected Publications (from about 140 refereed publications):
i. Last five years:
1. “Semiparametric GEE analysis in partially linear single-index models for longitudinal data,” Annals of Statistics, to appear. With J. Chen, et al.
2. “A new nonparametric stationarity test of time series in time domain,” Journal of the Royal Statistical Society,
Ser. B, to appear. With L. Jin and H. Wang.
3. “Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study,”
Briefings in Bioinformatics, to appear. With M. Fan, et al.
4. “Children’s active commuting to school: an interplay of self-efficacy, social economic disadvantage, and
environmental characteristics,” International Journal of Behavioral Nutrition and Physical Activity, to appear.
With W. Lu, et al.
5. “A Laplace method for under-determined Bayesian experimental designs,” Computer Methods in Applied
Mechanics and Engineering, (2015), 285, 849–876. With Q. Long, et al.
6. “Semiparametric approach for non-monotone missing covariates in a parametric regression model,” Biometrics, (2014), 70, 299–311. With S. Sinha and K. K. Saha.
7. “A framework for scalable parameter estimation of gene circuit models using structural information,” Bioinformatics, (2013), 29, i98–i107. With H. Kuwahara, et al.
8. Maximum Likelihood Estimation for Sample Surveys, (2012), Chapman & Hall, New York. With R. L. Chambers, et al.
9. “A goodness-of-fit test of logistic regression models for case-control data with measurement errors,” Biometrika,
(2011), 98, 877–886. With G. Xu.
1
284
10. “Generalized empirical likelihood methods for analyzing longitudinal data,” Biometrika, (2010), 97, 79–93.
With L. Qian and R. L. Carroll.
ii. Other Noteworthy Publications:
1. “Partially linear models with missing response variables and error-prone covariates,” Biometrika, (2007), 94,
185–198. With H. Liang and R. J. Carroll.
2. “Estimation in partially linear models with missing covariates,” Journal of the American Statistical Association, (2004), 99, 357–367. With H. Liang, et al.
3. “Smoothing spline estimation in varying coefficient models,” Journal of the Royal Statistical Society, Ser. B,
(2004), 66, 653–667. With R. L. Eubank, et al.
4. “Saddlepoint approximations as smoothers,” Biometrika, (2002), 89, 933–938. With A. C. Davison.
5. “High-order accurate methods for retrospective sampling problems,” Biometrika, (1999), 86, 881–897. With
R. J. Carroll.
6. “Limited information likelihood analysis of survey data,” Journal of the Royal Statistical Society, Ser. B,
(1998), 60, 397–411. With R. L. Chambers and A. H. Dorfman.
7. “Weighted semiparametric estimation in regression analysis with missing covariate data,” Journal of the American Statistical Association, (1997), 92, 512–525. With C. Y. Wang, et al.
8. “A new estimator for the finite population distribution function,” Biometrika, (1996), 83, 639–652. With A.
H. Dorfman.
9. “Saddlepoint expansions in finite population problems,” Biometrika, (1993), 80, 583–590.
10. “Tail probability approximations in the first-order noncircular autoregression,” Biometrika, (1992), 79, 431–
434.
Grants in last five years:
i. Last five years:
1. U.S. Food and Drug Administration (2014–2015, Co-I.)
2. Scott&White Healthcare Research Grants Program Vision Award (2014–2015, Co-I.)
3. Robert Wood Johnson Foundation Childhood Obesity Prevention Program (2008–2015, Co-I.)
4. TAMU Institute of Applied Mathematics and Computational Science Innovation Award (2012–2013, P.I.)
5. Scott&White Healthcare Research Grants Program Vision Award (2012–2014, Co-I.)
6. NIH National Center on Minority Health and Health Disparities (2007–2012, Co-I.)
7. NIH National Institute of Mental Health (2009–2011, Co-P.I.)
8. National Space Biomedical Research Institute (2008–2012, Co-I.)
ii. Other Noteworthy Grants:
1. National Multiple Sclerosis Society (subcontract) (2003–2006, P.I.)
2. National Institute of Environmental Health Sciences Center Grant (1998–2007, Co-P.I.)
3. National Multiple Sclerosis Society (subcontract) (2003–2005, P.I.)
4. National Multiple Sclerosis Society (2001–2003, Co-P.I.)
5. Texas Advanced Research Program (2000–2002, P.I.)
6. National Multiple Sclerosis Society (2000–2003, Co-P.I.)
7. TAMU Interdisciplinary Research Initiatives Program (1998–1999, P.I.)
8. National Security Agency (1996–1998, P.I.)
2
285
9.
10.
11.
12.
13.
National Science Foundation (1995–1997, P.I.)
TAMU Program to Enhance Scholarly and Creative Activities (1995–1996, P.I.)
ASA/NSF/BLS Senior Research Fellowship (1994, P.I.)
National Science Foundation (1992–1994, P.I.)
Texas Advanced Research Program (1991–1994, P.I.)
Awards and Honors: Please annotate as space allows
1. Australian National University Mathematical Sciences Research Visiting Fellowship Award, 2013
2. Texas A&M University Student Led Award for Teaching Excellence, 2011
3. Texas A&M University System-wide Teaching Excellence Award, 2010
4. University-level Distinguished Achievement Award in Teaching, Texas A&M University, 2005
5. Texas A&M University Faculty Fellow, 2002-2007
6. Elected Fellow of the Institute of Mathematical Statistics, 2001
7. Elected Member of the International Statistical Institute, 2000
8. Elected Fellow of the American Statistical Association, 2000
9. College-level Distinguished Achievement Award in Teaching, Texas A&M University, 1997
10. ASA/NSF/BLS Senior Research Fellowship, 1994
11. Editor-in-Chief of Journal of Nonparametric Statistics (2007–2012)
12. Member of Editorial Boards:
Biometrics (1997–2005)
Communications in Statistics (1995–2001)
InterStat (1995–2009)
Journal of Nonparametric Statistics (2004–2007, 2013–)
Statistics & Probability Letters (2014–)
Service: Please annotate as space allows
1. Review Panelist for the National Science Foundation (multiple times, most recent in 2015)
2. Chair of the ASA Journal of Nonparametric Statistics Editor-in-Chief Search Committee, 2015
3. Board of Directors of the International Chinese Statistical Association, 2005–2008
4. Board of Governors of the Zhejiang University Alumni Association, 2011–2016
5. President, Vice-President, Secretary of the Southeast Texas Chapter of the American Statistical Association, 1991–
94
6. External Examiner for a Habilitation thesis at University of Bern, Switzerland
7. External Examiner for Ph.D. theses at Monash University, Australia, University of Geneva, Switzerland, Mangalore
University, India, University of Sydney, Australia, and University of Wollongong, Australia
Students Supervised:
Supervised or co-supervised 21 Ph.D. students and 20 M.S. students.
On over 90 other graduate student supervisory committees.
3
286
THOMAS WEHRLY
Education:
University of Michigan–Ann Arbor
University of Wisconsin–Madison
University of Wisconsin–Madison
Appointments:
Professor
Visiting Research Fellow
Associate Professor (Visiting)
Associate Professor
Assistant Professor
Mathematics
Mathematics
Statistics
B.S. (1969)
M.S. (1970)
Ph.D. (1976)
Department of Statistics,Texas A& M University
Stat. Research Sect., Australian National University
Department of Statistics, University of North Carolina
Department of Statistics, Texas A&M University
Department of Statistics, Texas A&M University
1988-Pres.
1990
1985
1982-1988
1976-1982
Publications:
i. Last five years:
1. Chen, Hsiang-Chun and Wehrly, Thomas, E. (2015), “Assessing Correlation of Clustered Mixed Outcomes
from a Multivariate Generalized Linear Mixed Model,” Statistics in Medicine, 34, 704-720.
ii. Other Noteworthy Publications:
1. Yu, J. and Wehrly, T. E., (2004) “An approach to the residence time distribution for stochastic multi-compartment
models”, Mathematical Biosciences, 191, 185-205.
2. Matis, J. H. and Wehrly, T. E. (1998), “A General Approach to Non-Markovian Compartmental Models”,
Journal of Pharmacokinetics and Biopharmaceutics, 26, 437-456
3. Cardwell, K. F. and Wehrly, T. E. (1997), “A Rank Test for Distinguishing Environmentally and Genetically
Induced Disease Resistance in Plant Varieties,” Biometrics, 53, 195-206.
4. Chambers, R. L., Dorfman, A. H. and Wehrly, T. E. (1993). “Bias Robust Estimation in Finite Populations
using Nonparametric Calibration,” Journal of the American Statistical Association, 88, 268-277.
5. J. Baek and T. E. Wehrly, (1993), “Kernel Estimation for Additive Models under Dependence,” Stochastic
Processes and Their Applications, 47, 95–112.
6. Hart, J. D. and Wehrly, T. E. (1992). “Kernel regression estimation when the boundary region is large with an
application to testing the adequacy of polynomial models,” Journal of the American Statistical Association,
87, 1018–1024.
7. Hall, P. G. and Wehrly, T. E. (1991). “A geometrical method for removing edge effects from kernel-type
nonparametric regression estimators,” Journal of the American Statistical Association, 86, 665-672.
8. Hart, J.D. and Wehrly, T.E. (1986). “Kernel regression estimation using repeated measurements data,” Journal
of the American Statistical Association, 81, 1080-1088.
9. LaRiccia, V.N. and Wehrly, T.E. (1985). “Asymptotic properties of a family of minimum quantile distance
estimators, Journal of the American Statistical Association, 80, 742-747.
Grants in last five years:
i. Last five years:
1. “UBM Integrated Undergraduate Experiences in Biological and Mathematical Sciences”, Vincent Cassone,
P.I., Thomas Wehrly one of 4 co-PIs, $499646, 5%, 9/15/04-8/31/11.
1
287
ii. Other Noteworthy Grants:
1. “Frontiers of Statistical Research: Forty Years of Statistics at Texas A&M University,” National Science
Foundation, $11250, T. E. Wehrly, P.I, 10/11/02-10/12/02.
2. “Nonparametric Estimation of Functions Based Upon Correlated Observations,” Office of Naval Research,
9/1/85-8/31/88, Renewed to 9/30/90. J. D. Hart, T. E. Wehrly, Co-Principal Investigators.
Awards and Honors: Please annotate as space allows
1. Member of Editorial Boards:
The American Statistician (1987–1993).
Statistics and Probability Letters (1982–2007).
2. Visiting Scholar:
Australian National University, Canberra, Australia, (January–May 1990).
Service:
1. Chair, Undergraduate Committee, Department of Statistics, 2013–14, chaired the committee responsible for the
proposal to Texas A&M University for an undergraduate degree in statistics.
2. Chair, Personnel and Tenure Committee 2009–13
3. Chair, Parzen Prize Committee, 2010–14.
4. Chair, Athletics Council, Texas A&M University, 2004–15.
5. Treasurer, Texas Kappa Chapter of Phi Beta Kappa at Texas A&M University, 2007–14.
6. Member, SEC Validation of Academic Credentials Review Committee, 2012–15
7. Member, University Disciplinary Appeals Panel, 2008–14.
8. Member, Faculty and Staff Interaction Team (multidepartment committee), 2013–14.
9. Member, Implementation Task Force for Athletics (President’s committee), 2010–11
10. Member, Vision 2020, Midterm Review Task Force: Imperative 4 Study Team, 2010–11
11. Member, President’s Task Force for Athletics, 2009–11
12. Member of departmental committees including Graduate Service Committee (2004–15), Graduate Program Committee (2005–14), Graduate Admissions Committee (2014–15), Department Head Search Committee (2013–14)
13. Speaker, Faculty Senate, Texas A&M University, 1999–2000.
Students Supervised:
1. Hsiang-chun Chen, Ph. D., August 2013. Inference for Clustered Mixed Outcomes from a Multivariate Generalized
Linear Mixed Model.
2. Nai-Wei Chen, Ph. D., December 2011. Goodness-of-Fit Test Issues in Generalized Linear Mixed Models.
3. Daniel Glab, Ph. D., May 2011. Testing Lack-of-Fit of Generalized Linear Models Via Laplace Approximation
4. Jihnhee Yu, Ph.D., August 2003. Approaches to the Multivariate Random Variables Associated with Stochastic
Processes.
2
288
5. Shao-Hung Wang, Ph.D., May 1995. A Data-Driven Smoothing Parameter Selection for Robust Nonparametric
Regression.
6. Shenq-Nah (Christine) Yang, Ph.D., December 1991. A Matrix Exponential and Bootstrap Analysis of Nonlinear
Least Squares Estimation for Compartmental Models.
7. Jangsun Baek, Ph.D., August 1991, Kernel Estimation for Nonparametric Additive Models.
8. Joey Ensor, Ph.D., August 1989, A Two-Compartment, Irreversible Flow Model with Clustering.
9. Eileen King, Ph.D., December 1988. A Test for the Equality of Two Regression Curves based on Kernel Smoothers.
(co-chair, J. D. Hart)
10. Joshua Baker, Ph.D., May 1985. Conditional Least Squares Estimation and Design for Continuous-Time Stochastic
Processes.
11. Vincent LaRiccia, Ph.D., December 1979. A Family of Minimum Quantile Distance Estimators.
Master’s students supervised over the last 5 years (13 Master’s students supervised during previous years):
1. Emily Seem, M.S., expected August 2015
2. Zachary Scott, M.S., May 2014
3. Huiwen Wilkerson, M.S., May 2014
4. Tara Cope, M.S., August 2013
5. Angela Brown, M.S., May 2013
6. Jennifer Whitten, M.S., December 2012
7. Michael Yingling, M.S., December 2012
8. Alexander Little, M.S., May 2012
9. Cynthia Franklin, M.S., May 2012
10. Karen Connelly, M.S., May 2012
3
289
LAN ZHOU
Education:
University of California at Berkeley
Beijing University, China
Beijing University, China
Appointments:
Associate Professor
Assistant Professor
Research Assistant Professor
Research Assistant Professor
Biostatistician
Statistical Consultant
Statistics
Probability and Statistics
Probability and Statistics
Ph.D. (1997)
M.A. (1992)
B.A. (1989)
Department of Statistics, Texas A&M University
Department of Statistics, University of Pennsylvania
Department of Statistics, University of Pennsylvania
Department of Statistics, University of Pennsylvania
Department of Biostatistics, CCEB, University of Pennsylvania
Analysis and Inference, Inc., Swarthmore, PA
2014-Present
2008-2014
2005-2008
2005
1998-2004
1998
Research Expertise:
Statistical methodology and application in bioinformatics, nutrition and epidemiology, spline/nonparametric smoothing,
functional and longitudinal data analysis
Publications:
i. Last five years:
1. Guo, M.† , Zhou, L.† , Huang, J. Z. and H¨ardle W. K. (2015) Functional data analysis of generalized quantile
regressions. Statistics and Computing, 25, 189–202. († contributed equally)
2. Assaad, H., Hou, Y., Zhou, L., Carroll, R. J., and Wu, G. (2015). Rapid publication-ready MS-word tables for
two-way ANOVA. SpringerPlus, 4:33.
3. Zhou, L. and Pan, H.∗ , (2014). Smoothing noisy data for irregular regions using penalized bivariate splines on
triangulations. Computational Statistics, Vol 29, 263–281. (∗ graduate student)
4. Zhou, L. and Pan, H.∗ (2014). Principal component analysis of two-dimensional functional data. Journal of
Computational and Graphical Statistics, Vol 23, 779–801. (∗ graduate student)
5. Cheng, G., Zhou, L., Chen, X. and Huang, J.Z. (2014). Efficient estimation of semiparametric copula models for
bivariate survival data. Journal of Multivariate Analysis, Vol 123, 330–344.
6. Cheng, G., Zhou, L. and Huang, J.Z. (2014). Efficient semiparametric estimation in generalized partially linear
additive models for longitudinal/clustered data. Bernoulli, Vol 20, 141–163.
7. Assaad, H., Yao, K., Tekwe, C.D., Feng, S., Bazer, F. W., Zhou, L., Carroll, R. J., Meininger, C. J. and Wu, G.
(2014). Analysis of energy expenditure in diet-induced obses rats. Frontiers in Bioscience, Vol 19: 967–985.
8. Assaad, H., Zhou, L., Carroll, R. J., and Wu, G. (2014). Rapid publication-ready MS-word tables for one-way
ANOVA. SpringerPlus, 3:474.
9. G. Wu, J. Zhu, J. Yu, L. Zhou, J. Z. Huang, and Z. Zhang (2014). Evaluation of five methods for genome-wide
circadian gene identification. Journal of Biological Rhythms, Vol 29, 231–242.
10. Jia, Q., Ivanov, I., Zlatev, Z. Z., Alaniz, R. C., Weeks, B. R., Callaway, E. S., Goldsby, J. S., Davidson, L. A., Fan,
Y., Zhou, L., Lupton, J. R., McMurray, D. N., Chapkin, R. S. (2011) Dietary fish oil and curcumin combine to
modulate colonic cytokinetics and gene expression in DSS-treated mice. British Journal of Nutrition, Vol 106(4),
519–29.
11. Zhou, L., Huang, J. Z., Martinez, J. G., Maity, A., Baladandayuthapani, V., Carroll., R. J.(2010) Reduced rank
mixed effects models for spatially correlated hierarchical functional data. Journal of American Statistical Association, Vol 105, 390–400.
1
290
12. Martinez, J. G., Liang, F., Zhou, L., Carroll, R. J. (2010) Longitudial functional principal component selection
via Stochastic Approximation Monte Carlo. Canadian Journal of Statistics, Vol 38, 256–270.
13. Wei, J.∗ and Zhou, L. (2010) Model selection using modified AIC and BIC in joint modeling of paired functional
data. Statistics & Probability Letters, Vol 80, 1918–1924. (∗ graduate student)
ii. Publications Before 2010:
1. Miki, A., Liu, G. T., Goldsmith, Z. G., Zhou, L., Siegfried, J., Hulvershorn, J., Raz, J., Haselgrove, J.C. (2001)
Effects of check size on visual cortex activation studied by functional magnetic resonance imaging. Ophthalmic
Research, 33, 180–184.
2. Huang, J. Z., Wu, C. O., Zhou, L. (2002) Varying coefficient models and basis function approximations for the
analysis of repeated measurements. Biometrika, 89, 111–128.
3. Renbaum L., Ufberg D., Sammel M., Zhou L., Jabara S., Barnhart K. T. (2002) Reliability of hysterosalpingogram
(HSG): Clinicians vs radiologists. Fertility and Sterility, 78, 614–618.
4. Hennessy S., Bilker, W. B., Zhou L., Weber, A. I., Brensinger C., Wang, Y., Strom, B. L. (2003) Retrospective drug
utilization review, prescribing errors, and clinical outcomes. The Journal of the American Medical Association,
29, 1494–1499
5. Norman, S., Localio, A. R., Zhou, L., Bernstein, L., Coates, R., Flagg, E., Marchbanks, P., Malone, K., Weiss, L.,
Lee, N., Nadel, M. (2003) Validation of self-reported screening mammography histories among women with and
without breast cancer. American Journal of Epidemiology, 158, 264–271.
6. Barnhart, K., Sammel, M. D., Rnaudo, P. F., Zhou, L., Guo, W., Hummel, A. C. (2004). BhCG doubling time
in symptomatic patients with an early intrauterine pregnancy: The curves redefined. Obstetrics and Gynecology,
104, 50–55.
7. Barnhart, K., Sammel, M. D., Chung, K., Zhou, L., Hummel, A. C., and Guo, W. (2004). Decline of serum
human chorionic gonadotropin and spontaneous complete abortion: defining the normal curve. Obstetrics and
Gynecology, 104, 975–981.
8. Huang, J. Z., Wu, C. O. and Zhou, L. (2004). Polynomial spline estimation and inference for varying coefficient
models with longitudinal data. Statistica Sinica, 14, 763–788.
9. Foulkes, A. S., Reilly, M., Zhou, L., Wolfe, M. and Rader, D. J. (2005) Mixed modelling to characterize genotypephenotype associations. Statistics in Medicine, 24, 775-789.
10. Norman, S. A., Localio, A. R., Zhou, L., Weber, A. L., Coates, R. J., Malone, K. E., Bernstein, L., Marchbanks,
P. A., Liff, J. M., Lee, N. C., Nadel, M. R. (2006) Benefit of screening mammography in reducing the rate of
late-stage breast cancer diagnosis (United States). Cancer Causes Control, 17, 921–929.
11. Chung K., Sammel M. D., Zhou L., Hummel A. C., Guo W., Barnhart K. (2006). Defining the curve when initial
levels of human chorionic gonadotropin in patients with spontaneous abortions are low. Fertility and Sterility, 85,
508–510.
12. Localio A. R., Zhou L., Norman S. A. (2006) Measuring screening intensity in case-control studies of the efficacy
of mammography. American Journal of Epidemiology, 164, 272–281.
13. Seeber B., Sammel M. D., Guo W., Zhou L., Hummel A. C., Barnhart K. T. (2006) Application of redefined hCG
curves for the diagnosis of women at risk for ectopic pregnancy. Fertility and Sterility, 86, 454–459.
14. Silva C., Sammel M. D., Zhou L., Gracia C., Guo W., Hummel A. C., Barnhart K. T. (2006) hCG profile for
Women with an Ectopic Pregnancy. Obstetrics and Gynecology, 107, 605–610.
15. Zhang P., Kim W., Zhou L., Wang N., Ly L. H., McMurray D. N., Chapkin R. S. (2006). Dietary fish oil inhibits
antigen-specific murine Th1 cell development by suppression of clonal expansion. Journal of Nutrition, 136(9),
2391–2398.
16. Azzoni L., Chehimi, J., Zhou, L., Foulkes, A. S., June, R., Maino, V. C., Landay, A., Rinaldo, C., Jacobson, L. P.,
Montaner, L. J. (2007) Early and delayed benefits of HIV-1 suppression: Timeline of recovery of innate immunity
effector cells. AIDS, 21, 293–305.
2
291
17. Huang, J. Z., Zhang, L., Zhou, L. (2007) Efficient estimation in marginal partially linear models for longitudinal/clustered data using splines. Scandinavian Journal of Statistics, 34, 451–477.
18. Matis, J. H., Zhou, L., Kiffe T. R., Matis T. I. (2007) Fitting cumulative size mechanistic models to insect population data: A nonlinear random effects model analysis. Journal of Indian Society of Agricultural Statistics, 61,
No. 2, 147-155.
19. Zhou, L., Huang, J. Z. Carroll, R. J. (2008) Joint modeling of paired sparse functional data using principal
components. Biometrika, 95, No. 3, 601-619
20. Fan Y. Y., Kim W., Callaway E., Smith R., Jia Q., Zhou L., McMurray D. N., Chapkin R. S. (2008) Fat-1
transgene expression prevents cell culture-induced loss of membrane n-3 fatty acids in activated CD4(+) T-cells.
Prostaglandins Leukot Essent Fatty Acids, 2008, 79, 209–214.
21. Qiao, Z.∗ , Zhou, L. and Huang, J. Z. (2008) Effective linear discriminant analysis for high dimensional, low
sample size data. Proceedings of 2008 World Congress of Engineering (WCE 2008), 1070–1075. (The Certificate
of Merit Award for The 2008 International Conference of Computational Statistics and Data Engineering, WCE
2008) (∗ graduate student)
22. Qiao, Z.∗ , Zhou, L. and Huang, J. Z. (2009) Sparse linear discriminant analysis for high dimensional, low sample
size data. IAENG International Journal of Computer Science, Vol 39, 48–60. (∗ graduate student)
23. Fan, Y. Y., Zhan, Y., Aukema, H. M., Davidson, L. A., Zhou, L., Callaway, E., Tian, Y., Weeks, B. R., Lupton,
J. R., Toyokuni, S., Chapkin, R. S. (2009) Proapoptotic effects of n-3 fatty acids are enhanced in colonocytes of
manganese-dependent superoxide dismutase knockout mice. Journal of Nutrition, Vol 139, 1328–1332.
Grants in last five years:
i. Last five years:
1. National Science Foundation (2009-2013), $262,106, “Statistical Methods for Complex Functional Data,” (PI)
Awards and Honors:
1. The Certificate of Merit Award, International Conference of Computational Statistics and Data Engineering, World
Congress of Engineering, 2008
for the paper “Effective linear discriminant analysis for high dimensional, low sample size data”
2. General Program Prize Paper, American Society for Reproductive Medicine, 2003
for the paper “Decline of serum human chorionic gonadotropin and spontaneous complete abortion: defining the
normal curve”
3. University of California, Berkeley: University Fellowship, 1992-1993
Service:
1. Referee for 18 journals
2. Organizer of Invited Session: Recent Advances in Longitudinal and Functional Data Analysis
International Chinese Statistical Association 2012 Applied Statistics Symposium, Boston, June 23-26, 2012.
Course Taught:
STAT 211 (Principles of Statistics), STAT 302 (Statistical Methods), STAT 627 (Nonparametric Function Estimation)
Ph.D. student advising committee:
Shuai Chen (Chair), Huijun Pan (Co-Chair), Andrew Middleton Redd, Adrian Barquero Sanchez, Yei Eun Shin, Ya Su (CoChair), Jiawei Wei (Co-Chair), Tae Ho Yoon
M.S. student advising committee:
Michael James Alzubaydi, Deron Aucoin (Chair), Dai Chen (Chair), Shuai Chen (Co-Chair), Cody Cox, Eric Frederiksen,
John J. Gosink (Chair), Barney Govan, Zhuoya He, Ming Jia, Geoffrey M. Lucas (Chair), Jennifer Phan, Eric Przybylinski
(Chair), Yiyi Wang, Yuen Sum S. Wong, Mi Zhang, Tinyi Zhu
3
292