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David Abel
(503) 329-0843
[email protected]
EDUCATION
Brown University, Providence, RI.
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Doctor of Philosophy in Computer Science (In Progress).
Master of Science in Computer Science (Completed, May 2015).
Focus in Artificial Intelligence, Machine Learning, and Robotics. GPA 4.0/4.0
Member of Humans to Robots Group, advised by Prof. Stefanie Tellex and Prof. Michael Littman.
Relevant Coursework: Machine Learning, Advanced Algorithms, Grounded Language for Robotics,
Cryptography, Data-driven Computer Vision and Graphics, Incompleteness (Metamathematics).
Carleton College, Northfield, MN.
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Sept. 2013 - Present
Sept. 2009 - June 2013
Bachelor of Arts in Computer Science and Philosophy, Magna Cum Laude.
Computer Science GPA: 3.8/4.0. Philosophy GPA: 3.8/4.0. Cumulative GPA: 3.7/4.0.
Distinction in Major & Thesis: Philosophy, Distinction in Major & Capstone: Computer Science.
Relevant Coursework: Algorithms, Theory of Computation, Artificial Intelligence, Natural Language
Processing, Math of Computer Science, Operating Systems, Linear Algebra, Computer Organization and
Architecture, Multivariable Calculus, Software Design, Programming Languages, Data Structures.
PROFESSIONAL EXPERIENCE
Brown University, Providence, RI.
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Graduate Research Assistant in Humans to Robots Laboratory. Led a research project in Machine
Learning and Robotics. First author on three associated scientific papers.
Teaching Assistant, First Byte of Computer Science. (w/ Prof. Michael Littman)
Teaching Assistant, Artificial Intelligence. (w/ Prof. Stefanie Tellex)
Qualcomm Inc, Boulder, CO.
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2014 - Present
Summers 2011 and 2012
Engineering Intern in DirectX Graphics Team, and Intern in Test team for Android.
Developed build sync tool that reduced time of a frequently used procedure from 8 hours to 5 seconds.
Implemented performance counters for Qualcomm's Adreno 320 GPU Architecture.
Automated build procedure for testing framework on Android devices.
Intel Corp, Hillsboro, OR.
Summers 2008, 2009, and 2010
Software Engineering Intern in Intel's Larrabee GPGPU group and Intern in Software and Services Group.
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Designed and built a performance testing suite for Intel Larrabee GPGPU.
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Developed add-on for parallel path-finding sample for Intel Larrabee SDK. Created wrapper that
analyzed the performance of different implementations of parallelized A*.
PROJECTS (available on github)
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Goal-Based Action Priors: Developed novel probabilistic planning & learning algorithms that scale to massive
domains. Associated papers published at ICAPS ’15, RSS ’14: First Workshop on Affordances, AAAI ’14: Fall
KSBT Symposium, presented at NEML ’14, NERC ’14. Completed in Humans to Robots Lab at Brown.
Lechuga: Built an extension for Google Chrome that visualizes browser usage statistics. Created at Hack@Brown
2014. Winner of “Best Visualization” prize. Completed at Brown, 2014.
ICS: Built a Scheme interpreter in C. Completed at Carleton College, 2012.
Skills: Extensive experience with Python and Java. Some experience with Scheme, Matlab, C, Prolog, C++.