Huan Lei

Huan Lei

Assistant Professor, Department of Computational Mathematics, Science and Engineering; Department of Statistics and Probability
Room 2502, Engineering Building
  428 S. Shaw Ln.
 (517) 432-0464
  leihuan@msu.edu

Education:
Ph. D. 2012, Applied Mathematics, Brown University
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
 

My research draws inspiration from a variety of scientific and engineering questions relevant to fluid dynamics, chemistry, material sciences, and climate physics. In particular I am interested in developing high-fidelity computational models for multiscale multiphysics systems that no longer fit into traditional hypothesis-driven based descriptions. Current research focuses on the development of numerical methods for integrating the model reduction and projection theory with data-learning algorithms to probe low-dimensional evolution dynamics relevant to diffusion, transport, transition, etc. The major object is to construct data-driven models encoded with nonlocal correlations and fluctuations arising from interactions on smaller scales juxtapose with proper physical constraints. The particular areas of application includes nanoscale and mesoscale hydrodynamics, coarse-grained molecular dynamics, material synthesis,  biomolecule modeling and climate modeling.

• Multiscale modeling 

• Stochastic modeling 

• Uncertainty quantification

[1]  H. Lei, J. Li, P. Gao, P. Stinis, and N. Baker. A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness. Computer Methods in Applied Mechanics and Engineering, 350:199 – 227, 2019 
 
[2]  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
 
[3]  H. Lei, X. Yang, B. Zheng, G. Lin, and N. A. Baker. Constructing surrogate models of complex systems with enhanced sparsity: Quantifying the influence of conformational uncertainty in biomolecular solvation. SIAM Multiscale Model. Simul., 13(4):1327–1353, 2015 
 
[4]  H. Lei and G. E. Karniadakis. Probing vaso-occlusion phenomena in sickle cell anemia via mesoscopic simulations. Proc. Natl. Acad. Sci., 110(28):11326–11330, 2013 
 
[5]  H. Lei, B. Caswell, and G. E. Karniadakis. Direct construction of mesoscopic models from microscopic simulations. Phys. Rev. E, 81:026704, 2010