I'm a PhD student in the Neural Networks Research Group at UT Austin. My main research interests are machine learning and game theory, particularly how we can use function approximators to scale to games with large state and action spaces. I spend most of my days working on algorithms for discovering Nash equilibria in stochastic, partial-information games like poker.
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.