Affiliations

• Applied Mathematics and Computational Science

Education Profile

• Ph.D. Cornell University, 1988
• M.A. Peking University, China, 1984
• B.A. Xiangtan University, China, 1982

Research Interests

Jinchao Xu is Director of KAUST Innovation Hub in Shenzhen, Professor of Applied Mathematics and Computational Sciences at King Abdullah University of Science and Technology, Director of KAUST-SRIBD Joint Lab for Scientific Computing and Machine Learning, Verne M. Willaman Professor of Mathematics and Director of the Center for Computational Mathematics and Applications at the Penn State University. Xu is an advocate of the idea that practical applications and theoretical completeness and beauty can go together. He studies numerical methods for partial differential equations and big data, especially finite element methods, multigrid methods, and deep neural networks, for their theoretical analysis, algorithmic development, and practical applications. More recently, he has been leading a collaborative effort on the development of Arabic Large Language Model (LLM), known as AceGPT, that has demonstrated most competitive performances among all open-source LLMs for Arabic language.

Selected Publications

• Iterative methods by space decomposition and subspace correction J Xu SIAM review 34 (4), 581-613
• Parallel multilevel preconditioners JH Bramble, JE Pasciak, J Xu Mathematics of computation 55 (191), 1-22
• Two-Grid Discretization Techniques for Linear and Nonlinear PDEs J Xu SIAM journal on numerical analysis 33 (5), 1759-1777
• A novel two-grid method for semilinear elliptic equations J Xu SIAM Journal on Scientific Computing 15 (1), 231-237
• Convergence estimates for multigrid algorithms without regularity assumptions JH Bramble, JE Pasciak, JP Wang, J Xu Mathematics of Computation 57 (195), 23-45