He is broadly interested in statistical theory and methodology and related areas of probability and machine learning, with specific expertise in random matrix theory, high dimensional and multivariate statistics, random graphs and networks, and discrete algorithms. Zhou spends part of his time working in statistical genetics at the Broad Institute. He completed his Ph.D. in Statistics at Stanford University, and formerly worked at D. E. Shaw Research where he developed statistical and software tools for molecular dynamics simulations of protein molecules.