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Lihao Zhang is a PhD student in the Department of Applied Mathematics & Statistics at Stony Brook University. His current work is centered on parallel Markov Chain Monte Carlo methods for optimization. He is focusing on both theoretical and empirical analysis for parallel simulated annealing. The goal of his work is to design a scalable parallel MCMC method with theoretical foundation. Also, he is interested in the application of MCMC method in different areas. He is exploring the different objective problems including cardinality constrained portfolio optimization and taxi sharing assignment. He is also very interested in the development of supercomputer. He visited Tianhe-2 in Guangzhou and TaihuLight in Wuxi, and wrote a review paper on the analysis of the fastest supercomputers. Before joining the PhD program in Stony Brook university, Lihao finished his Master program in Rutgers University on Financial Statistics and Risk Management. He received his Bachelor degree in Mathematics in Wuhan University, China. He had research experience in National Supercomputer Center in Jinan during the summer from 2014 to 2017.
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