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Bhavya Kailkhura
4-206 Center of Science & Technology, Syracuse University, Syracuse NY 13244
[email protected]
(315) 744-5313
http://bkailkhu.mysite.syr.edu
SUMMARY
Doctoral student with 3 years of experience in the fields of high-dimensional data analysis, signal processing, machine
learning, optimization and their applications to solve inference problems with security & privacy constraints. Over
15 papers (including 9 journal publications) published and/or submitted in various refereed journals and conferences.
EDUCATION
Syracuse University, Syracuse, NY, USA
Ph.D. in Electrical and Computer Engineering
Advisor: Pramod K. Varshney
2012 - 2016 (Expected)
Syracuse University, Syracuse, NY, USA
M.S. in Electrical Engineering
2010-2012
Nagpur University, Nagpur, India
B.E. in Electrical Engineering
2006 - 2010
SCHOLASTIC ACHIEVEMENTS
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Runner-up for Best Student Paper Award in IEEE Asilomar Conf. on Signals, Systems & Computers, 2014.
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Graduate award for outstanding performance by Department of EECS, Syracuse University.
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Several awards in science exhibitions and project competitions.
RESEARCH EXPERIENCE
EECS DEPARTMENT, SYRACUSE UNIVERSITY, Syracuse, NY.
Research Assistant, Advisor: Pramod K. Varshney, (Aug. 2012–present)
Distributed Inference from Corrupted Data
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Conducting research on design and analysis of robust inference systems (see Publications).
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Typical inference systems considered are detection, classification or estimation using distributed nodes.
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Existence of unreliable nodes (Byzantines) in the network result in degraded performance.
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Machine learning and statistical signal processing schemes are used to mitigate the effects of Byzantines.
Statistical Inference for High-Dimensional Data with Secrecy Guarantees
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Design of efficient signal processing techniques exploiting lower dimensional structures (see Publications).
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Solution methodology exploits lower dimensional signal processing techniques to solve inference problems.
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Artificial noise injection techniques are used to improve the secrecy performance.
Automatic Large-Scale Classification of Bird Sounds
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Huge amount of data collected at three NEON sites : Harvard Forest, Massachusetts; Central Plains Experimental Research Station, Colorado; and Sterling, Colorado.
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Analysis of existing unsupervised feature learning techniques such as spherical k-means clustering.
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Dictionary learning and sparse coding based techniques are used for robust classification.
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Currently, applying deep learning based techniques for improving the classification performance.
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Bhavya Kailkhura
Center for Advanced Systems and Engineering (CASE), SYRACUSE UNIVERSITY, Syracuse, NY.
Research Intern, (March 2011–July 2012)
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Cyber Cross-Layer Optimize Publish-Subscribe Cognitive Networking System (Cyclops): Merged
the benefits of access control list (ACL) in capability based system to utilize complementary capabilities of
both approaches, while avoiding obvious disadvantages of ACL.
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Designed better generation, verification and revocation algorithms for our system, which was implemented
on a Linux based system.
PUBLICATIONS
JOURNAL ARTICLES
1. B. Kailkhura, S. Brahma, Y. S. Han, and P. K. Varshney, “Distributed Detection in Tree Topologies with
Byzantines,” IEEE Trans. Signal Process., vol. 62, no. 12, pp. 3208-3219, June 15, 2014.
2. B. Kailkhura, Y. S. Han, S. Brahma, and P. K. Varshney, “Asymptotic Analysis of Distributed Bayesian
Detection with Byzantine Data,” IEEE Signal Process. Lett., vol. 22, no. 5, pp. 608-612, May 2015.
3. B. Kailkhura, A. Vempaty, and P. K. Varshney, “Distributed Inference in Tree Networks using Coding
Theory,” to appear in IEEE Trans. Signal Process.
4. B. Kailkhura, Y. S. Han, S. Brahma, and P. K. Varshney, “Distributed Bayesian Detection with Byzantine
Data,” to appear in IEEE Trans. Signal Process.
5. B. Kailkhura, S. Brahma, B. Dulek, Y. S. Han, and P. K. Varshney, “Distributed Detection in Tree-based
Topologies: Byzantines and Mitigation Techniques,” to appear in IEEE Trans. Inf. Forensics and Security.
6. B. Kailkhura, V. Sriram Siddhardh (Sid) Nadendla, and P. K. Varshney, “Distributed Inference in the
Presence of Eavesdroppers: A Survey,” to appear in IEEE Comm. Magazine.
7. B. Kailkhura, S. Brahma, and P. K. Varshney, “Consensus based Detection in the Presence of Data Falsification Attacks,” IEEE Trans. Sig. Process., under review.
8. B. Kailkhura, Thakshila Wimalajeewa, and P. K. Varshney, “Collaborative Compressive Detection with
Physical Layer Secrecy Constraints,” IEEE Trans. Inf. Theory, under review.
9. B. Kailkhura, S. Liu, Thakshila Wimalajeewa, and P. K. Varshney, “Measurement Matrix Design for
Compressive Detection with Secrecy Guarantees,”, IEEE Signal Process. Lett., under review.
CONFERENCE PAPERS
1. B. Kailkhura, S. Brahma, and P. K. Varshney, “Optimal Byzantine Attacks on Distributed Detection
in Tree-based Topologies,” to appear in Proc. International Conference on Computing, Networking and
Communications (ICNC 2013), San Diego, USA, 2013.
2. B. Kailkhura, S. Brahma, Y. S. Han, and P. K. Varshney, “Optimal Distributed Detection in the Presence of
Byzantines,” to appear in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing
(ICASSP), Vancouver, Canada, May 2013.
3. B. Kailkhura, Y. S. Han, S. Brahma, and P. K. Varshney, “On Covert Data Falsification Attacks on
Distributed Detection Systems,” to appear in Proc. 13th International Symposium on Communications and
Information Technologies (ISCIT 2013), Samui Island, Thailand, Sep. 2013.
4. B. Kailkhura, S. Brahma, and P. K. Varshney, “On Performance Analysis of Data Fusion schemes with
Byzantines,” to appear in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing
(ICASSP), 2014.
5. B. Kailkhura, L. Shen, T. Wimalajeewa, and P. K. Varshney, “Distributed Compressive Detection with
Perfect Secrecy,” to appear in 2nd International Workshop on Compressive Sensing in Cyber-Physical Systems
(CSCPS).
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Bhavya Kailkhura
6. V. Gupta, B. Kailkhura, Thakshila Wimalajeewa, and P. K. Varshney, “Joint Sparsity Pattern Recovery
with 1-bit Compressive Sensing in Distributed Sensor Networks,”, submitted to 49th Asilomar Conf. on
Signals, Systems and Computers, Pacific Grove, CA.
INVITED CONFERENCE PAPERS
1. B. Kailkhura, T. Wimalajeewa, and P. K. Varshney, “On Physical Layer Secrecy of Collaborative Compressive Detection,” to appear in 48th Asilomar Conf. on Signals, Systems and Computers, Pacific Grove, CA.
(Runner-up Best Student Paper Contest)
CONFERENCE PAPERS (In Preparation)
1. B. Kailkhura, V. Sriram Siddhardh (Sid) Nadendla and P. K. Varshney, “Optimal Distributed Detection
with Byzantines: A Game-Theoretic Perspective,” in preparation.
SERVICE & PROFESSIONAL ACTIVITIES
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Session Organizer/Chair: IEEE Asilomar Conf. on Signals, Systems and Comp. (Asilomar CSSC).
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Member: IEEE, IEEE Signal Processing Society, IEEE Communications Society.
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Reviewer: IEEE Communications Letters, IEEE Transactions on Information Forensics and Security, IEEE
International Conference on Communications (ICC).
PROGRAMMING & SOFTWARE SKILLS
Programming & Software: MATLAB, C/C++, Python, Java, Verilog/VHDL.
Operating Systems: Linux, Microsoft Windows.
REFERENCES
Available upon request.
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