Meta Research

I am the Engineering Manager for Meta’s Probabilistic Programming Languages team. Our goal is to platformize Bayesian modeling and analysis within Meta, and invest energy and research into cutting-edge techniques that rely on compiler-driven analyses in order to advance the performance and reliability universal Bayesian inference. We have a diverse team, ranging from Programming Language experts, modeling veterans, algo/optimization specialists, and Systems hackers. I am particularly interested in using program analysis with variational inference in order to customize and scale inference to huge data sets while retaining the ergonomics and developer friendliness of a general-purpose programming language.