He completed his undergraduate and graduate work at Stanford University, obtaining a B.S. in Mathematics in 2003, an M.S. in Electrical Engineering in 2004, and a Ph.D. in Statistics in 2009. For his dissertation he worked with Art Owen, studying applications of cross-validation to unsupervised learning. Between 2009 and 2011 he worked with Patrick Wolfe as a postdoctoral researcher at Harvard University. His research is primarily in modern multivariate statistics. Specifically, it focuses on inference for network data and other emerging data sources, high-dimensional data analysis, and random matrix theory. He's also interested in data visualization and statistical computing.