Lester Mackey

À propos

I’m a statistical machine learning researcher at Microsoft Research New England (opens in new tab) and an adjunct professor at Stanford University. 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. Before joining Microsoft, I spent three wonderful years as an assistant professor of Statistics (opens in new tab) and, by courtesy, Computer Science (opens in new tab) at Stanford and one as a Simons Math+X (opens in new tab) postdoctoral fellow, working with Emmanuel Candes (opens in new tab). My Ph.D. advisor was Mike Jordan (opens in new tab), and my undergraduate research advisors were Maria Klawe (opens in new tab) and David Walker (opens in new tab). I got my first taste of research at the Research Science Institute (opens in new tab) and learned to think deeply of simple things at the Ross Program (opens in new tab).

My current research interests include statistical machine learning, scalable algorithms, high-dimensional statistics, approximate inference, and probability. Lately, I’ve been developing and analyzing scalable learning algorithms for healthcare, climate forecasting, approximate posterior inference, high-energy physics, recommender systems, and the social good (opens in new tab).

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 (opens in new tab).

For more details about my interests and work please see my external website (opens in new tab).