I am an Assistant Professor in the Department of Mathematics at the University of California, Riverside. Previously, I was a postdoc at the Illinois Institute of Technology, working with Prof. Chun Liu. I obtained my Ph.D. at Peking University, advised by Prof. Pingwen Zhang, in 2018. Prior to that, I received a B.S. from Zhejiang University.
Broadly speaking, my research lies at the intersection of variational modeling, scientific computing, and machine learning, with applications in physics, materials science, biology, and data science. I am particularly interested in developing multiscale, thermodynamically consistent variational models and structure-preserving numerical methods for complex dissipative systems, including liquid crystals, polymeric fluids, reaction–diffusion processes, and biological systems. More recently, I have been exploring how machine learning can enhance variational modeling and computation, by learning unknown dynamics, constructing coarse-grained closures, improving traditional numerical methods and solving high-dimensional PDEs. I'm also interested in investigating variational perspectives on machine learning, interpreting learning dynamics as dissipative systems governed by energy–dissipation laws and designing algorithms inspired by structure-preserving numerical discretizations.
2009 - 2013, B.S., School of Mathematical Sciences, Zhejiang University, China.
2013 - 2018, Ph.D., School of Mathematical Sciences, Peking University, China.
Advisor: Prof. Pingwen Zhang.
Thesis: Numerical Study of Topological Defects in Liquid Crystals Under the Geometric Constraints
2022 - now : Assistant Professor, Department of Mathematics, University of California, Riverside.
2018 – 2022: Postdoc, Department of Applied Mathematics, Illinois Institute of Technology.
Mentor: Prof. Chun Liu.
PI, NSF DMS Grant #2410740, "Collaborative Research: Energetic Variational-Based Numerical Studies in Complex Fluids with Thermo-Chemo-Mechanical Effects", 09/15/2024–08/31/2025.
Co-PI, NSF DMS Grant #2153029, "Energetic Variational Inference: Foundations, Algorithms, and Applications", 07/01/2022–06/30/2024 (PI: Prof. Lulu Kang; Co-PI: Prof. Chun Liu, Illinois Institute of Technology). The grant was transferred to Grant #2429324 following the PI’s institutional move.
Yiwei Wang*. Energetic variational modeling of active nematics: coupling the Toner-Tu model with ATP hydrolysis. arXiv preprint arXiv:2506.23043, 2025.[arxiv]
Xuelian Bao, Chun Liu, and Yiwei Wang*. A deterministic–particle–based scheme for micro-macro viscoelastic flows. J. Comput. Phys. 522 (2025): 113589.
Ziqing Hu, Chun Liu, Yiwei Wang*, and Zhiliang Xu. Energetic Variational Neural Network Discretizations of Gradient Flows. SIAM J. Sci. Comp., 46(4), A2528-A2556, 2024.
Yiwei Wang, Jiuhai Chen, Chun Liu and Lulu Kang*. Particle-based energetic variational inference. Stat Comput 31, 34 (2021).[pdf]
Yiwei Wang*, Teng-Fei Zhang, Chun Liu. A two-species micro-macro model of wormlike micellar solutions and its maximum entropy closure approximations: An energetic variational approach. J Non-newton Fluid Mech, 2021.[arXiv][pdf]
Chun Liu, Cheng Wang, and Yiwei Wang*. A Structure-preserving, operator splitting scheme for reaction-diffusion equations with detailed balance. J. Comput. Phys, Vol 436, 110253, 2021.[pdf]
Chun Liu and Yiwei Wang*. On Lagrangian schemes for porous medium type generalized diffusion equations: a discrete energetic variational approach. J. Comput. Phys., Vol. 417, 109566, 2020. [pdf]
Chun Liu and Yiwei Wang*. A variational Lagrangian scheme for a phase field model: A discrete energetic variational approach. SIAM J. Sci. Comp. , 42(6), B1541–B1569, 2020. [pdf]
Yiwei Wang*, Chun Liu, Pei Liu, and Bob Eisenberg. Field theory of reaction-diffusion: Mass action with an energetic variational approach. Phys. Rev. E 102, 062147, 2020. [pdf]
Yiwei Wang, Pingwen Zhang*, and Jeff Z. Y. Chen*. Topological defects in an unconfined nematic fluid induced by single and double spherical colloidal particles. Phys. Rev. E, 96(4):042702, 2017. [pdf]
Yiwei Wang, Pingwen Zhang*, and Jeff Z. Y. Chen*. Formation of three-dimensional colloidal crystals in a nematic liquid crystal. Soft Matter, 2018. [pdf]
Yiwei Wang, Giacomo Canevari, and Apala Majumdar*. Order reconstruction for nematics on squares with isotropic inclusions: A Landau–de Gennes study. SIAM J. Appl. Math., 79(4):1314–1340, 2019. [pdf]
JungHyun Noh, Yiwei Wang, Hsin-Ling Liang, Venkata Subba Rao Jampani, Apala Majumdar*, and Jan P. F. Lagerwall*. Dynamic tuning of the director field in liquid crystal shells using block copolymers. Phys. Rev. Research, 2:033160, 2020.
Jianyuan Yin, Yiwei Wang, Jeff Z. Y. Chen*, Pingwen Zhang*, and Lei Zhang*. Construction of a pathway map on a complicated energy landscape. Phys. Rev. Lett., 124(9):090601, 2020. [arxiv]