Professor, Ph.D., 1989, Columbia University
Molecular Dynamics; Parallel Computing
Yuefan Deng's research involves developing parallel computing and machine learning algorithms, and implementing them on the latest supercomputer architectures, for a wide range of scientific problems. He has been, since 2010s, focusing efforts on the development of a multi-scale model for the dynamics of human platelets' activation, aggregation, and interactions with the flow and the vascular wall. He is a specialist in parallelizing the Markov Chain Monte Carlo optimization techniques with broad applications in engineering and finance as well as medicine. He is the winner of the 2016 SUNY Chancellor's Award for Excellence in Teaching. He has supervised 22 Ph.D. theses and is popular among the 12,000+ students who have taken his AMS 361.
Office: Physics A-135