I’m a researcher at Microsoft Research New England and an adjunct professor of Statistics at Stanford University. I spent three wonderful years as an assistant professor of Statistics and, by courtesy, Computer Science at Stanford and one as a Simons Math+X postdoctoral fellow, working with Emmanuel Candes at Stanford. I received my Ph.D. in Computer Science (2012) and my M.A. in Statistics (2011) from UC Berkeley and my B.S.E. in Computer Science (2007) from Princeton University. My Ph.D. advisor was Mike Jordan, and my undergraduate research advisors were Maria Klawe and David Walker.
My current research interests include statistical machine learning, algorithms and data structures, high-dimensional statistics, and concentration inequalities. Lately, I’ve been developing and analyzing scalable learning algorithms for healthcare, recommender systems, approximate posterior inference, high-energy physics, and the social good.
Quixotic though it may sound, I hope to use computer science and statistics to change the world for the better. If you have thoughts on how to do this, feel free to contact me.
For more details about my interests and work please see my external website.