Lijun Ding

Lijun Ding is an Assistant Professor specializing in optimization and data science at UC San Diego. He received his Ph.D. in Operations Research from Cornell University in 2021 and teaches courses in optimization and data science.

His research focuses on continuous optimization methods, particularly semidefinite programming and applications in statistics. Prior to joining UCSD, he was an assistant professor at Texas A&M University and a post-doctoral scholar at the Institute of Foundations of Data Science.

Recent publications demonstrate his work in developing efficient algorithms for large-scale optimization problems, with applications in machine learning and statistical signal processing. His articles frequently explore convergence properties of optimization methods and novel formulations for challenging mathematical programs.