Wesley Tansey


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I'm a Computer Science PhD candidate at UT Austin working with James Scott. My main research interests are health and wellness applications of machine learning, particularly those involving graphical models, Bayesian statistical methods, and scalable inference algorithms. My current projects include obesity and nutrition modeling, wearable devices for fitness tracking, and large-scale multiple hypothesis testing for fMRI and allele frequency studies.

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 and was a quant at a hedge fund.



Diet2Vec: Multi-scale analysis of massive dietary data
W. Tansey, E. W. Lowe, and J. G. Scott
The 2016 NIPS Workshop on Machine Learning for Health, December 2016. [paper]

Better conditional density estimation for neural networks
W. Tansey, K. Pichotta, and J. G. Scott
arXiv:1606.02321, June 2016. [preprint] [code coming soon... email me until then]


Multiscale spatial density smoothing: an application to large-scale radiological survey and anomaly detection.
W. Tansey, A. Athey, A. Reinhart, and J. G. Scott
arXiv:1507.07271, July 2015. [preprint] [code] (currently undocumented but supported in the GFL package)

A Fast and Flexible Algorithm for the Graph-Fused Lasso.
W. Tansey and J. G. Scott.
arXiv:1505.06475, May 2015. [preprint] [code]

Vector-Space Markov Random Fields via Exponential Families.
W. Tansey, O.-H. Madrid-Padilla, A. Suggala, and P. Ravikumar.
In International Conference on Machine Learning (ICML) 32, 2015. [pdf] [code]


False Discovery Rate Smoothing.
W. Tansey, O. Koyejo, R. A. Poldrack, and J. G. Scott.
arXiv:1411.6144, November 2014. [preprint] [code]


Accelerating Evolution via Egalitarian Social Learning.
W. Tansey, E. Feasley, and R. Miikkulainen.
The 14th Annual Genetic and Evolutionary Computation Conference (GECCO'12), Philadelphia, Pennsylvania, USA, July 2012. [pdf] [code]

Multiagent learning through neuroevolution.
R. Miikkulainen, E. Feasley, L. Johnson, I. Karpov, P. Rajagopalan, A. Rawal, and W. Tansey.
Advances in Computational Intelligence, pages 24-46, 2012.

(-\infty, 2012)

Trailblazer: A Tool for Automated Annotation Refactoring.
M. Song, E. Tilevich, and W. Tansey.
An OOPSLA 2009 Tool Demo.

DeXteR - An Extensible Framework for Declarative Parameter Passing in Distributed Object Systems.
S. Gopal, W. Tansey, G. C. Kannan, and E. Tilevich.
In Proceedings of ACM/IFIP/USENIX 9th International Middleware Conference (Middleware 2008), 2008. [pdf]

Annotation Refactoring: Inferring Upgrade Transformations for Legacy Applications.
W. Tansey and E. Tilevich.
In The 2008 ACM SIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA 2008), October 2008. [pdf]

Efficient Automated Marshaling of C++ Data Structures for MPI Applications.
W. Tansey and E. Tilevich.
In Proceedings of the 22nd Annual IEEE International Parallel and Distributed Processing Symposium (IPDPS 2008), April 2008. [pdf]