Assistant Professor of Statistics and Data Science
Zhou Fan’s research focuses on statistical theory and methodology, and related areas of probability and machine learning. Fan’s expertise lies in random matrix theory, high dimensional and multivariate statistics, random graphs and networks, and discrete algorithms. In recent years, his works have been published by The Annals of Statistics, Probability Theory and Related Fields; Statistica Sinica; Symposium on Theory of Computing (STOC); among others. Fan completed his Ph.D. in Statistics at Stanford University and spent a summer working on statistical genetics at the Broad Institute before joining Yale’s faculty. Prior to obtaining his Ph.D., he worked for two years at D. E. Shaw Research developing statistical and software tools for molecular dynamics simulations of protein molecules.