His research focuses on adapting ideas from machine learning to statistical problems that arise in scientific applications. He is particularly interested in causal inference, non-parametric statistics, uses of subsampling for data analysis, and empirical Bayes methods. More He received his Ph.D. in Statistics from Stanford University in 2016, and also holds a B.Sc. (2011) degree in Mathematics from Stanford. He was a postdoctoral researcher at Columbia University during the academic year 2016-2017, and has worked with or consulted for several Silicon Valley companies, including Dropbox, Facebook and Google.