Yuefan Deng | |
|---|---|
 Deng in 1983 | |
| Born | December 26, 1962 Hubei Province, China |
| Alma mater | Nankai University Columbia University |
| Scientific career | |
| Fields | Applied Mathematics |
| Institutions | Stony Brook University Hong Kong University of Science and Technology Columbia University National University of Singapore New York University |
| Doctoral advisor | Norman H. Christ |
Yuefan Deng (Y. F. Deng, Chinese: 邓越凡; pinyin: Dèng Yuèfán, born December 1962) is a computational scientist, academic, and author serving as a Professor in the Department of Applied Mathematics and Statistics at Stony Brook University.[1] His research centers on developing parallel computing and machine learning algorithms for supercomputers, with a particular focus on modeling human platelet dynamics and optimizing Markov Chain Monte Carlo techniques for various applications.[2]
Deng's publications comprise journal articles and textbooks including Lectures, Problems and Solutions for Ordinary Differential Equations, Introductory Partial Differential Equations and Applied Parallel Computing. He received 2015-2016 Stony Brook University Dean’s Award and the 2016 State University of New York Chancellor's Award for Excellence in Teaching.[3]