Dr. Bai's primary research interests include linear algebra algorithm design, analysis and software engineering for solving large-scale matrix computation problems in science and engineering. He is one of developers of LAPACK, a software library for solving the most common problems in numerical linear algebra and templates for the solution of algebraic eigenvalue problems. His current research work focuses on synergistic activities in designing numerical linear algebra theory algorithms for applications in computational science and engineering, such as minimization principles in the linear response theory, rapid iterative diagonalization in ab initio electronic structure calculations, and communication-reducing algorithms for graded matrix decompositions for many-body quantum Monte Carlo simulations on GPU accelerated multicore computer systems. He serves on multiple editorial boards of journals in his research field, including Journal of Computational Mathematics and ACM Transactions on Mathematical Software. Dr. Bai holds a joint appointment with the Department of Computer Science at UC Davis.
