Xiang Zhou

Xiang Zhou joins the FAS as Professor of Statistics and Data Science. His research centers on genomic data science, with a focus on developing innovative statistical and machine learning methodologies—including deep learning and artificial intelligence tools—for the analysis of large-scale, high-dimensional genetic and genomic data. His work spans a range of application areas, including genome-wide association studies, single-cell sequencing, and spatial multi-omics. Prior to joining Yale, Zhou was Professor of Biostatistics at the University of Michigan, where he also served as Assistant Director of AI & Digital Health Innovation. He earned his BS from Peking University in 2004 and his MS (2009) and PhD (2010) from Duke University. He completed postdoctoral training at the University of Chicago (2010–2013), where he subsequently served as the Williams H. Kruskal Instructor in the Department of Statistics (2013–2014). Zhou is a Fellow of the American Statistical Association, and he is the recipient of the 2024 Mid-career Biosciences Faculty Achievement Recognition (MBioFAR) Award and the 2025 ICIBM Eminent Scholar Award. He is a standing member of the NIH MRAA Study Section and currently serves as an Associate Editor for PLOS Genetics, the Journal of the American Statistical Association, and Annals of Applied Statistics.