I'm an assistant professor of Statistics and (by courtesy) Computer Science at Stanford University. Previously, I was a Simons Math+X postdoctoral fellow, working with Emmanuel Candes 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. 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, high-dimensional statistics, algorithms and data structures, and concentration inequalities. Lately, I've been developing and analyzing algorithms for ranking, admixtures, matrix factorization, and collaborative filtering and crafting concentration inequalities for random matrices. I'm also organizing a working group on Statistics for Social Good. My interest lies, more generally, in problems that bridge applications and theory and that involve drawing inferences from large, structured datasets.
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.
- Jessica Hwang