معرفی
Yang Feng is a Professor and Ph.D. Program Director in the Department of Biostatistics at New York University's School of Global Public Health. He holds affiliate faculty positions at the Center for Data Science and PRIISM. His research focuses on Machine Learning, High-Dimensional Statistics, Network Models, and Applications in Biostatistics and Public Health.
Key contributions include advancements in Neyman-Pearson classification, federated learning, transfer learning, and high-dimensional statistical methods. He has authored influential papers in journals such as the Annals of Statistics, JASA, and Journal of Machine Learning Research.
- Recipient of prestigious honors: ASA Fellow, IMS Fellow, and ISI Elected Member.
- Leading an NSF-funded project on high-dimensional multi-task learning inference (Grant DMS-2324489).
- Editorial roles at top journals including JASA and AOAS.
Research emphasizes theoretical foundations and practical applications, spanning statistical methodology, algorithm development, and interdisciplinary collaborations in health and data science.
