Lijun Ding ( joined the University of Wisconsin-Madison (UW-Madison) in September 2022 as an IFDS postdoc with Stephen J. Wright. Before joining IFDS at UW-Madison, He was an IFDS postdoc with Dmitry Drusvyatskiy, and Maryam Fazel at the University of Washington. He obtained his Ph.D. in Operations Research at Cornell University, advised by Yudong Chen and Madeleine Udell.  

Lijun’s research lies at the intersection of optimization, statistics, and data science. By exploring ideas and techniques in statistical learning theory, convex analysis, and projection-free optimization, he analyses and designs efficient and scalable algorithms for classical semidefinite programming and modern nonconvex statistical problems. He also studies the interplay between model overparametrization, algorithmic regularization, and model generalization via the lens of matrix factorization. He plans to explore a wider range of topics at this intersection during his appointment at UW-Madison.

He is on the 2022 – 23 job market!