Dr. Xu’s research is in sparse modeling and statistical learning. His interests include feature screening, distributed learning, high-dimensional regression, subsampling, and statistical computing. Recently, he focuses on developing efficient processing methods for big data, where traditional methods are less helpful due to the high computational burden. His works emphasize on both theoretical and computational aspects, which have a wide application scope in various disciplines.





