University of Houston
Ming Zhong
Assistant Professor · Department of Mathematics
Learning governing structure in scientific data.
About
I am an Assistant Professor in the Department of Mathematics at the University of Houston. My research lies at the intersection of inverse problems, scientific machine learning, learning dynamical systems, and numerical analysis.
Before joining the University of Houston in 2024, I was an Assistant Professor at Illinois Institute of Technology, an Assistant Research Scientist at the Texas A&M Institute of Data Science, and a postdoctoral researcher at Johns Hopkins University. I received my Ph.D. in Applied Mathematics from the University of Maryland.
I am a co-principal investigator on the NSF project A Bayesian Paradigm for Physics-Informed Machine Learning and received a Ralph E. Powe Junior Faculty Enhancement Award for data-driven modeling of emergent behavior in social science.
News
- Jan. 2027Joint Mathematics Meetings Upcoming
With Chunyang Liao (UCLA), I am co-organizing the AMS Special Session on Recent Advances in Scientific Machine Learning: Theory, Algorithms, and Applications at JMM 2027 in Chicago on January 14, where I will also give a talk, Recent Advances in Learning Collective Behavior.
- Nov. 2026SIAM Mathematics of Data Science Upcoming
On November 18, I will speak on understanding collective behaviors at SIAM MDS in Salt Lake City.
- Oct. 2026Three SIAM sectional meetings
I spoke on crime dynamics at the SIAM NY-NJ-PA Sectional Meeting at Rutgers and on training PINNs for stiff and hyperbolic PDEs at SIAM Central States at Jackson State University. At the SIAM TX-LA Sectional Meeting at SMU, I co-organized the mini-symposium Learning-Based Methods for Differential Equations: Mathematical Foundations and Computational Algorithms (MS 13) with Chunyang Liao (UCLA) and Min Wang (Simon Fraser University) and hosted its Friday afternoon and Saturday morning sessions; my student Joseph Dingillo spoke in the Friday session.
- Sep. 2026Two new preprints
Physics-informed random feature neural networks for solving PDEs (with C. Chen and C. Liao) and learning interaction kernels from collective steady states (with B. Hao and M. Maggioni) are now on arXiv.
- Jul. 2026Congratulations, Dr. Ziheng Guo!
Ziheng defended his thesis on system identification of stochastic dynamics in May and graduated in July. He has joined Wells Fargo as an Assistant Vice President in quantitative research.
Contact
- University email
- mzhong3@central.uh.edu
- Office
- PGH 616
- Department
- Department of Mathematics
- Address
- University of Houston
Houston, TX 77204