XU, Luze

XU, Luze is an Assistant Professor in the Department of Mathematics at The Hong Kong University of Science and Technology. He received his Ph.D. in Industrial and Operations Engineering from the University of Michigan in 2022, advised by Prof. Jon Lee. Prior to joining HKUST, he served as a Krener Assistant Professor at the University of California Davis from 2022 to 2025 and as a Postdoctoral Research Associate at the University of Wisconsin-Madison in 2025. His research interests include mixed integer programming, global optimization, and the connections between continuous and discrete optimization. He teaches MATH2350 Applied Linear Algebra and Differential Equations.

Luze Xu KAP is a researcher at the University of California, Davis, with a focus on optimization. Their work explores advanced techniques in optimization, particularly in the context of integer programming, generalized inverses, and structured sparsity. Xu's research includes the development of algorithms for polynomial bounds, proximity analysis, and the design of efficient methods for solving complex optimization problems. They have also contributed to the study of Δ-modular integer programs, sparse reflexive generalized inverses, and the analysis of convex functions. Their publications highlight the intersection of theoretical and applied optimization, emphasizing the importance of structured sparsity and proximity bounds in improving computational efficiency.