Hongchao Zhang receives NSF funding for research on Optimization Theory

Hongchao Zhang LSU Department of Mathematics Professor Hongchao Zhang was recently awarded a grant from the National Science Foundation (NSF) for his research into optimization methods for nonconvex structured optimization. Dr. Zhang’s research interests involve nonlinear optimization theory, algorithms and their applications, sparse matrix computing, graph partitioning, stochastic optimization algorithms and applications, and numerical linear algebra. His research previously received funding by the NSF for work on inexact optimization methods for structured nonlinear optimization, acceleration techniques for lower-order algorithms in nonlinear optimization, and the analysis and design of gradient methods for large-scale nonlinear optimization and applications. 

In 2013, Dr. Zhang received the LSU Rainmaker award as an Emerging Scholar, recognized for his innovative research and creative scholarship, and he received the McGehee Award for Excellent Research in 2016. He was the Industrial Postdoctoral Fellow at the Institute for Mathematics and Its Applications (IMA) at the University of Minnesota, and IBM Thomas J. Watson Research Center. Zhang received his Ph.D. from the University of Florida in 2006, his M.S. degree in applied mathematics from the Chinese Academy of Sciences in 2001, and his B.S. degree in computational mathematics from Shandong University, China in 1998. Dr. Zhang has held a joint position with the Center for Computation and Technology (CCT) and the Department of Mathematics since 2008. He serves on the editorial board of Springer’s Optimization Letters and Computational Optimization and Applications, and Journal of the Operations Research Society of China, as well as the American Institute of Mathematical Sciences Numerical Algebra, Control and Optimization. 

Contact: Jolie Cornay and Landon Troxclair

Photo: Bogdan Oporowski