Xiaofeng Xu
Biography
Xiaofeng Xu is a Ph.D. candidate in the AMCS program at KAUST, under the supervision of Professor Jinchao Xu. His research lies at the intersection of traditional numerical methods for partial differential equations (PDEs) and modern machine learning approaches. He is particularly interested in developing efficient and provably convergent training algorithms for neural networks in numerical PDEs.
Xiaofeng received his Bachelor's degree in Mathematics and Computer Science with First Class Honors from the Hong Kong University of Science and Technology (HKUST), and his Master’s degree from the Pennsylvania State University.
Research Interests
Xiaofeng Xu research focuses on the intersection of traditional numerical methods for partial differential equations (PDEs) and modern machine learning approaches. He is particularly interested in developing efficient and provably convergent training algorithms for neural networks in numerical PDEs.
