In fall 2020, I began my Ph.D. studies in Computational Mathematics, Science, and Engineering at Michigan State University. My journey in this field started with a bachelor's degree in Mathematics and Applied Mathematics from Soochow University, which I completed in July 2020. During my undergraduate studies, I focused on Computational Chemistry and Machine Learning under the guidance of Professor . In spring 2019, I participated in the UC Berkeley Extension Program, enhancing my knowledge and skills. The following summer, I joined a research internship at HKUST, working with Professor , which allowed me to delve deeper into my research interests. Additionally, in fall 2019, I had the opportunity to work on the Discontinuous Galerkin Method as a visiting student at the University of Massachusetts Dartmouth, under Professor Zheng Chen.

Research Interest

Machine learning methodology for multiscale modeling (model reduction)

Manybody Non-Markivan Dissipative Particle Dynamics, State-dependent General Lagenvin Dynamics.

Algorithms of Scientifc Machine learning

Mixed Redisual Method, Deep Learning Based Discontinuous Galerkin Method

Gradient free optimization method

Consensus based optimization, Consensus based Sampling.