Rate My Professor Xiaoliang Wan

Xiaoliang Wan is a Professor in the Department of Mathematics and affiliated with the Center for Computation and Technology at Louisiana State University. He earned his Ph.D. in Mathematics from Brown University in 2007, M.S. in Mathematics from Peking University in 2001, and B.S. in Mathematics from Peking University in 1998. Prior to his tenure-track positions, he served as a Joint Postdoctoral Research Associate at Brown University and MIT from 2007 to 2008, and as a Postdoctoral Research Associate in the Program in Applied and Computational Mathematics at Princeton University from 2008 to 2009. At Louisiana State University, his career progressed from Visiting Assistant Professor in Mathematics/CCT (2008-2009), to Assistant Professor (2009-2015), Associate Professor (2015-2021), and Professor since 2021. He also participated as a Member at the NSF Institute for Computational and Experimental Research in Mathematics (ICERM) in Providence, RI, during Fall 2012.

Professor Wan's research specializations include scientific machine learning, stochastic modeling, numerical methods for stochastic partial differential equations, adaptivity in numerical simulations, and the minimum action method for large deviation principles. Additional interests encompass numerical methods for uncertainty quantification, minimum action methods for rare event simulation, adaptive numerical solutions of stochastic differential equations, and deep learning and machine learning applications in computational physics and mathematics. Key publications feature 'An adaptive multi-element generalized polynomial chaos method for stochastic differential equations' (2005, with G.E. Karniadakis), 'Multi-element generalized polynomial chaos for arbitrary probability measures' (2006, with G.E. Karniadakis), 'The multi-element probabilistic collocation method (ME-PCM): Error analysis and applications' (2008, with J. Foo and G.E. Karniadakis), 'DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations' (2023, with K. Tang and C. Yang), 'Adaptive deep density approximation for Fokker-Planck equations' (2022, Journal of Computational Physics, with K. Tang and Q. Liao), 'A minimum action method for dynamical systems with constant time delays' (2021, SIAM Journal on Scientific Computing, with J. Zhai), and 'A dynamic-solver-consistent minimum action method: With an application to 2D Navier-Stokes equations' (2017, Journal of Computational Physics, with H. Yu). He received the LSU Council on Research Summer Stipend Program award in 2010. His scholarly contributions have notably advanced methodologies in stochastic modeling and computational mathematics.