Huan Lei

Associate Professor, Department of Computational Mathematics, Science and Engineering

Associate Professor, Department of Statistics & Probability

Location: 1501 Engineering Bldg

Phone: 517-884-8947

Email: leihuan@msu.edu

Website: https://leihuan-mp.github.io/

Photo of: Huan Lei

Bio

My research focuses on computational mathematics, particularly on developing numerical methods for learning partial differential equation (PDE) and stochastic differential equation (SDE) models arising from multi-scale problems. I am interested in designing structure-preserving algorithms that retain essential mathematical properties, such as conservation laws, variational structures, and physical constraints. A central aspect of my work is integrating scientific machine learning (SciML) with numerical analysis to construct accurate and physically interpretable PDE and SDE models of multi-scale systems directly from first-principle descriptions, where conventional approaches often show limitations.



Research Interests
===
+ Multi-scale modeling
+ Structure-preserving PDE models and numerical schemes
+ Model reduction and stochastic simulations
+ Scientific machine-learning

###Education
Ph. D. 2012, Applied Mathematics, Brown University - Advisor:  George Karniadakis
B.S. 2005, Special Class for the Gifted Young, Univ. of Science & Technology of China

###Professional Appointment
Post-doctoral Associate, Brown University (2012 -2013)
Post-doctoral Associate, Pacific Northwest National Laboratory (2013 -2015)
Scientist, Pacific Northwest National Laboratory (2015 -2019)


###Openings
One Ph.D. position is available starting in Fall 2027 in scientific machine learning and numerical analysis. If you are interested, please contact me by email.

Courses

STT 441: Prob & Stat I Probability

Selected Publications

H. Lei, N. A. Baker, and X. Li. Data-Driven Parameterization of the Generalized Langevin Equation. *Proc. Natl. Acad. Sci.* 113 (50):14183–14188, 2016 View Publication
L. Lyu and H. Lei. Consensus-Based Adaptive Sampling and Approximation for High-Dimensional Energy Landscapes *SIAM Journal on Scientific Computing*, 48(5), B751-B775, 2026 View Publication
L. Lyu and H. Lei. Construction of coarse-grained molecular dynamics with many-body non-Markovian memory. *Phys. Rev. Lett.* 131:177301, 2023 View Publication
P. Ge, Z. Zhang, and H. Lei. Data-driven learning of the generalized Langevin equation with state-dependent memory. *Phys. Rev. Lett.* 133:077301, 2024 View Publication
W. E, H. Lei, P. Xie, and L. Zhang. Machine learning-assisted multi-scale modeling. *Journal of Mathematical Physics*, 64(7):071101, 2023 View Publication
Y. Zhao and H. Lei, Fast spectral separation method for kinetic equation with anisotropic non-stationary collision operator retaining micro-model fidelity, *Journal of Computational Physics*, 565, 115205, 2026 View Publication
Y. Zhao, J. Burby, A. Christlieb and H. Lei. Data-Driven Construction of a Generalized Kinetic Collision Operator from Molecular Dynamics. *Phys. Rev. Lett.*, 135, 185101, 2025 View Publication