bio
Yang Feng is a Professor of Biostatistics in the School of Global Public Health at New York University, where he is also affiliated with the Center for Data Science. He earned his Ph.D. in Operations Research from Princeton University in 2010. His research centers on the theoretical and methodological foundations of machine learning, high-dimensional statistics, network models, and nonparametric statistics, with applications in Alzheimer’s disease prognosis, cancer subtype classification, genomics, electronic health records, and biomedical imaging, enabling more accurate models for risk assessment and clinical decision-making. He has published over 70 peer-reviewed papers across leading journals in statistics, machine learning, econometrics, public health, and medicine. His work has been supported by grants from the National Institutes of Health and the National Science Foundation (NSF), including the NSF CAREER Award. He currently serves as Associate Editor for several leading journals, including the Journal of the American Statistical Association (JASA), the Journal of Business & Economic Statistics, the Journal of Computational & Graphical Statistics, and the Annals of Applied Statistics. In addition, he will serve as Review Editor for JASA and The American Statistician from 2026 to 2028. His professional recognitions include being named a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, as well as an elected member of the International Statistical Institute.