Yuefan Deng
Professor, Ph.D., 1989, Columbia University
Molecular Dynamics; Parallel Computing  
Yuefan Deng’s research spans two highly synergistic aspects of computational science:
                        algorithm development and scientific applications. At the forefront of data science
                        and machine learning, he designs algorithms to manage multiple spatial and temporal
                        scales, enabling optimal simulations of complex phenomena such as human platelet dynamics
                        and the structures and functions of proteins of varying sizes. He also implements
                        these algorithms on modern supercomputers equipped with tens of thousands of CPUs
                        and GPUs. For years, Deng has worked on advancing and accelerating simulated annealing
                        algorithms—both sequential and parallel—expanding their applications across engineering,
                        finance, and medicine. He has supervised over 30 Ph.D. dissertations and is a highly
                        regarded instructor, having taught AMS 361 (Ordinary Differential Equations) to more
                        than 20,000 students. His excellence in teaching has earned him the 2016 SUNY Chancellor's
                        Award for Excellence in Teaching and the 2015–2016 Dean’s Award in Teaching.
 
Office: Physics A-135
Phone: 631-632-8614
https://you.stonybrook.edu/yuefandeng
