Date(s) - November 03, 2023
10:40 am - 11:30 am

Weil Hall 406

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Shuzhong Zhang profile picture

Shuzhong Zhang
Date : Friday, November 3, 2023
Mode : In-Person
Affiliation: University of Minnesota
Bio: Visit Page


Title : “Variational Inequality Problems Revisited”

Abstract : The Variational Inequality (VI) model is a general form of many scientific computing problems, including continuous optimization, saddle-point equilibria, complementarity problems, and computational games. As such, it is of fundamental importance. Recent years have seen the rising popularity of gradient-methods for optimization due to machine learning and AI applications. In this talk we discuss the extensions of gradient-type methods to the VI formulation. Our discussion includes finding the conditions for some non-monotone VI, under which our proposed new algorithms will converge to the solution as required, with guaranteed rates of convergence. Shuzhong Zhang, Ph.D. “Variational Inequality Problems Revisited”

Bio : Dr. Shuzhong Zhang is Professor and Founding Department Head of the Department of Industrial and System Engineering, University of Minnesota. He received a B.Sc. degree in Applied Mathematics from Fudan University in 1984, and a Ph.D. degree in Operations Research and Econometrics from the Tinbergen Institute, Erasmus University, in 1991. Prior to the current position, he had held faculty positions at University of Groningen (1991-1993), Erasmus University (1993-1999), and The Chinese University of Hong Kong (1999-2010). He received the Erasmus University Research Prize in 1999, the CUHK ViceChancellor Exemplary Teaching Award in 2001, the SIAM Outstanding Paper Prize in 2003, the IEEE Signal Processing Society Best Paper Award in 2010, and the 2015 SPS Signal Processing Magazine Best Paper Award. Dr. Zhang was an elected Council Member at Large of the MPS (Mathematical Programming Society) (2006-2009) and served as Vice-President of the Operations Research Society of China (ORSC) (2008-2012). He had served (or is serving) on the Editorial Board of several scholarly journals including SIAM Journal on Optimization, Management Science, and Operations Research. His research interests cover optimization, Operations Research, Machine Learning, Decision Science and Data Science in a broadly defined sense. He has written extensively on these topics. According to the 1st edition of the top scientists ranking published by in 2022, he was ranked one of the world’s top 1000 Scientists in the field of Mathematics.