He received his Ph.D. from Harvard University in 2014, supported by a NSF Graduate Fellowship. From 2014 to 2016, he was a Simons research fellow at U.C. Berkeley and a postdoc fellow at Microsoft Research. His research has been supported by awards from NSF, Gates Foundation, Simons Foundation. James develops machine learning algorithms for messy data and applies these new methods to extract disease insights from human population genomics. His work establishes rigorous mathematical foundations for messy data approaches and creates efficient software that has been widely used in disease analysis studies. Read more about Dr. Zou