I'm a PhD student in the Neural Networks Research Group at UT Austin. My main research interests are machine learning and Bayesian statistical methods, particularly how we can use big data to discover and recommend better treatments for patients with chronic illness. I spend most of my days working on algorithms to create personalized, adaptive treatments from patient health logs. If successful, these techniques may be able to improve the lives of millions of people living with chronic disease, as well as making substantial advances in the field of reinforcement learning.
In a previous life, I was a software engineering researcher working with Eli Tilevich at Virginia Tech, where I got my BS and MS in Computer Science. My Master's thesis focused on inference techniques that learn transformation rules to automatically upgrade legacy applications to use the latest version of a given API. I've also co-founded a couple of startups (EffectCheck, Curvio) and was a quant at a hedge fund.
Wesley Tansey, Eliana Feasley, and Risto Miikkulainen, "Accelerating Evolution via Egalitarian Social Learning," The 14th Annual Genetic and Evolutionary Computation Conference (GECCO 2012), Philadelphia, Pennsylvania, USA, July 2012. [Code]
Risto Miikkulainen, Eliana Feasley, Leif Johnson, Igor Karpov, Padmini Rajagopalan, Aditya Rawal, and Wesley Tansey, "Multiagent learning through neuroevolution." Advances in Computational Intelligence, pages 24-46, 2012.
Myoungkyu Song, Eli Tilevich, and Wesley Tansey, "Trailblazer: A Tool for Automated Annotation Refactoring," An OOPSLA 2009 Tool Demo.
Sriram Gopal, Wesley Tansey, Gokulnath C. Kannan, and Eli Tilevich, "DeXteR - An Extensible Framework for Declarative Parameter Passing in Distributed Object Systems," Proceedings of ACM/IFIP/USENIX 9th International Middleware Conference (Middleware 2008).
(Acceptance rate 18%)
Wesley Tansey and Eli Tilevich, "Annotation Refactoring: Inferring Upgrade Transformations for Legacy Applications," the 2008 ACM SIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA 2008).
(Acceptance rate 28%)
Wesley Tansey and Eli Tilevich, "Efficient Automated Marshaling of C++ Data Structures for MPI Applications," Proceedings of the 22nd Annual IEEE International Parallel and Distributed Processing Symposium (IPDPS 2008), April 2008.
(Acceptance rate 25%)