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Zhennan Zhou,Ph.D.

Math                Website:

Scientific Computing and Model AnalysisEmail:zhouzhennan@westlake.edu.cn

Biography

Zhennan Zhou graduated from the School of Mathematics at Jilin University in 2009 with a Bachelor's degree. In 2014, he obtained a Ph.D degree from the Department of Mathematics at the University of Wisconsin-Madison in the United States. From 2014 to 2017, he served as an Assistant Research Professor at Duke University in the United States. Between 2017 and 2023, he held the position of Assistant Professor at the Beijing International Center for Mathematical Research, Peking University. He joined the Westlake University in March 2024.

Research

Zhennan Zhou’s primary research interests lie in the applied analysis of differential equations and stochastic models, as well as the design and analysis of numerical methods for scientific problems. These problems stem from diverse fields such as quantum mechanics, theoretical chemistry, and biology, and often involve multiscale phenomena. He particularly focuses on strategies related to model reduction and efficient simulation techniques. Additionally, he takes interest in selected data-driven research topics.

Representative Publications

1. J. Carrillo, X. Dou andZ. Zhou, A simplified voltage-conductance kinetic model for interacting neurons and its asymptotic limit,SIAM Journal on Mathematical Analysis 2024 56:1, 676-726.

2. S. Jin, L. Li, X. Ye andZ. Zhou, Ergodicity and long-time behavior of the Random Batch Method for interacting particle systems,Mathematical Models and Methods in Applied Sciences, Vol. 33, No. 01, pp. 67-102 (2023).

3. J. Lu, Y. Lu andZ. Zhou, Continuum limit and preconditioned Langevin sampling of the path integral molecular dynamics,Journal of Computational Physics423 (2020): 109788, arXiv: 1811.10995.

4. J.-G. Liu, M. Tang, L. Wang andZ. Zhou, An accurate front capturing scheme for tumor growth models with a free boundary limit,Journal of Computational Physics, 364 (2018): 73-94.

5. J. Lu andZ. Zhou, Frozen Gaussian approximation with surface hopping for mixed quantum-classical dynamics: A mathematical justification of surface hopping algorithms,Mathematics of Computation(2018), 87.313, 2189-2232.