Wesley Tansey

abqox0@r.postjobfree.com 804-***-****

**** ******** **** **., ******, TX

http://cs.utexas.edu/~tansey

Research Statement

I m a PhD student at UT Austin interested in scaling machine learning techniques to real-

world domains. My main research is on algorithms for discovering Nash equilibria in full-scale

multiplayer poker. If successful, these techniques may have signi cant consequences for the

next-generation smart energy grid and other reinforcement learning systems.

I am passionate about companies and ideas that have the potential to be hugely disruptive.

I m currently looking for a summer internship as a data scientist or software engineer at such

a company.

Education

2011 Present Pursuing PhD in Computer Science, University of Texas at Austin

GPA 3.45

Graduate Coursework:

Graphical Models, Neural Networks,

Natural Language Processing, Reinforcement Learning

Mathematical Logic, Computer Security, Programming Languages

2006-2008 MS in Computer Science, Virginia Tech

GPA 3.81

2003-2006 BS in Computer Science, Virginia Tech

GPA 3.55

Select Publications

2012 W. Tansey, E. Feasley, and R. Miikkulainen. Accelerating evolution via egalitarian social

learning. In Proceedings of the Fourteenth International Conference on Genetic and Evolu-

tionary Computation Conference (GECCO 2012), pages 919 926. ACM, 2012

2012 R. Miikkulainen, E. Feasley, L. Johnson, I. Karpov, P. Rajagopalan, A. Rawal, and

W. Tansey. Multiagent learning through neuroevolution. Advances in Computational In-

telligence, pages 24 46, 2012

2008 W. Tansey and E. Tilevich. Annotation refactoring: inferring upgrade transformations for

legacy applications. In Proceedings of the 23rd ACM SIGPLAN Conference on Object-

Oriented Programming Systems, Languages, and Applications (OOPSLA 2008), volume 43,

pages 295 312. ACM, 2008

2008 W. Tansey and E. Tilevich. E cient automated marshaling of C++ data structures for MPI

applications. In Proceedings of the 2008 IEEE International Symposium on Parallel and

Distributed Processing (IPDPS 2008), pages 1 12. IEEE, 2008

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Work Experience

Currently Research Assistant, UT Austin

In the Neural Networks group led by Risto Miikkulainen

Researching evolutionary game theory and population dynamics for solving large-scale

stochastic games of partial information (poker). Co-wrote grant that earned funding from

the NSF s BEACON Center for the Study of Evolution in Action.

2011-2012 Co-founder, Curvio

Built, launched, and iterated a consumer web startup.

Organically grew site to 2k uniques/day. Managed a team of 12 remote contractors and

hundreds of turkers.

2011 Teaching Assistant, Computer Science Department, UT Austin

Participated in developing course materials for hundreds of students.

Helped setup up competition for AI MOOC class taught by Peter Norvig. Directly managed

team of four undergrad researchers.

2010 Co-founder, E ectCheck

Created novel machine learning algorithms for sentiment analysis.

Worked all areas of the business: front-end, back-end, sales, partnerships, and marketing.

2010-2011 Machine Learning Contractor, Natural Selection Financial

Researched adaptive machine learning models for quantitative nance.

Developed algorithms that explore huge data sets and discover exploitable patterns in market

prices.

2008-2010 Research Associate, Lincoln Vale Adaptive Strategies (Hedge Fund)

Researched and implemented machine learning algorithms for automated trading.

Developed 20+ real-world trading algorithms, with millions of dollars wagered on their pre-

dictions every day.

Skills

Python, Ruby, MATLAB, R, C#, C/C++, Java, HTML, CSS, and Javascript

Technical writing, team leadership, startups, games

Building systems to collect, clean, analyze, and learn from data

Awards and Miscellanea

Recipient of NSF Beacon Grant

NSF GRFP, Honorable Mention in Machine Learning category

Outstanding Graduate Student Award, Virginia Tech

Finished the San Diego Rock n Rock Marathon in 5:38:11

Projects available on my website: http://cs.utexas.edu/ tansey

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