Jiequn Han

I am a Research Scientist at the Center for Computational Mathematics, Flatiron Institute. Previously, I worked as an Instructor of Mathematics at the Department of Mathematics, Princeton University. I obtained my Ph.D. degree in applied mathematics from the Program in Applied and Computational Mathematics (PACM), Princeton University in June 2018, advised by Prof. Weinan E. Before that, I received my Bachelor degree from the School of Mathematical Sciences, Peking University in July 2013. I did a research internship in DeepMind during the summer of 2017, under the mentorship of Thore Graepel.

I conduct research on machine learning for science, drawing broadly from the methodologies and challenges of various scientific disciplines, with a focus on solving high-dimensional problems in scientific computing, primarily those related to PDEs and generative modeling. My research has been recognized with the SIAM Computational Science and Engineering (CSE) Early Career Prize (awarded biennially to one scholar).