Peimeng Yin

Assistant Professor   Department of Mathematical Sciences   The University of Texas at El Paso   Email: pyin@utep.edu    (No longer use yinp@ornl.gov !!!)                 URL: Github Homepage   URL: ORNL Homepage   Google Scholar   ResearchGate   ORCID       CyMail Google       Gmail Baidu       Outlook Library       Office Lib       Overleaf Citrix       Cybox UCAMS       Okta Tokens   MathSciNet   Python Software CFD-Lab   Wolfram Matlab

Biography

Dr. Peimeng Yin is an Assistant Professor in the Department of Mathematical Sciences at the University of Texas at El Paso (UTEP). He received his Ph.D. degree in the Department of Mathematics from Iowa State University in 2019 under the supervision of Prof. Hailiang Liu and Prof. Songting Luo. Prior to joining UTEP, he worked as a Postdoctoral Research Associate in Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL), a Research Assistant Professor (research-track) in the Department of Radiation Oncology at the University of Kansas Medical Center, and a Post-Doc Fellow in the Department of Mathematics at Wayne State University.

He works in the area of Computational Mathematics and Applied Mathematics with the main focus on Numerical Analysis, Partial Differential Equations, Scientific Computing, and Data Science. His work reflects a strong interplay of rigorous mathematical analysis, the design and implementation of accurate and efficient numerical algorithms for partial differential equations (PDEs), and their applications to physics, astrophysics, engineering, biology, energy, and oncology. His research interests focus on advanced numerical methods for modern PDE challenges, such as high derivatives, maximum principle preserving, singularities, high dimensions and multiscale.

Research Interests

• Discontinuous Galerkin finite element methods

• Structure preserving numerical methods

• Dynamical low rank approximations

• Time integration for gradient flows

• Efficient numerical methods for multiscale problems

• Theoretical and computational methods for singular elliptic PDEs

• Mathematical theory of deep learning and PDE-based data-driven modeling.

Selected recent work

• Yaoyao Chen, Hailiang Liu, Nianyu Yi and Peimeng Yin*. Unconditionally energy stable IEQ-FEMs for the Cahn-Hilliard equation and Allen-Cahn equation. Numerical Algorithms, to appear, 2024. [PDF] [DOI] [arXiv]

• Huini Liu, Nianyu Yi and Peimeng Yin*. A conservative relaxation Crank-Nicolson finite element method for the Schrödinger-Poisson equation. arXiv preprint, arXiv:2405.12848, 2024. [arXiv]

• Peimeng Yin*, Eirik Endeve, Cory D. Hauck and Stefan R. Schnake. Towards dynamical low-rank approximation for neutrino kinetic equations. Part I: analysis of an idealized relaxation model. Mathematics of Computation, DOI: https://doi.org/10.1090/mcom/3997, 2024. [PDF] [DOI] [arXiv]

• Hengguang Li, Peimeng Yin* and Zhimin Zhang. A $C^0$ finite element method for the biharmonic problem with Navier boundary conditions in a polygonal domain. IMA Journal of Numerical Analysis, 43:1779-1801, 2023. [PDF] [DOI] [arXiv]

• Hailiang Liu, Zhongming Wang, Peimeng Yin and Hui Yu. Positivity-preserving third order DG schemes for Poisson--Nernst--Planck equations. Journal of Computational Physics, 452:110777, 2022. [PDF] [DOI]

Available RA Positions

Dr. Peimeng Yin, from the Department of Mathematical Sciences at the University of Texas at El Paso, is seeking doctoral graduate students with focus on applied math, numerical analysis, and scientific computing. If you are interested, please contact Dr. Yin via pyin@utep.edu.