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, also at NYU. He earned his Ph.D. in Operations Research from Princeton University in 2010. His research focuses on machine learning, high-dimensional statistics, network models, and their applications in healthcare and public health, including Alzheimer's disease and cancer research. His work is funded by NIH and NSF grants, notably the NSF CAREER Award.
His research interests include theoretical and methodological advancements in machine learning, statistical theory, and computational methods, with applications to biomedical data analysis. He serves as an Associate Editor for major journals like JASA, JBES, and AoAS. His recognitions include ASA and IMS Fellowships and ISI election.
- Education: Ph.D. in Operations Research, Princeton University (2010)
Dr. Feng’s grants include NSF DMS-2324489 on high-dimensional transfer learning. He collaborates on projects like federated learning theory and clinical outcome prediction in neuro-oncology. His lab develops statistical tools for omics data analysis and public health surveillance.
Awards:
- Fellow, American Statistical Association (ASA)
- Fellow, Institute of Mathematical Statistics (IMS)
- Elected Member, International Statistical Institute (ISI)
He advises research teams on statistical methodology and data science applications. His work bridges theoretical statistics with practical challenges in healthcare analytics and computational biology.
