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     Chen Xiaoli,  a Special Professor at China University of Geosciences (Wuhan). She was selected as an Top young talents of CUG Scholar (Class A) and Hubei Provincial High-Level Talent Program(2024). She holds a PhD in Statistics from Huazhong University of Science and Technology (HUST), where her doctoral training included a collaborative program with Brown University. Prior to joining CUG, she served as a Research Fellow at the National University of Singapore (NUS). Her research bridges stochastic dynamical systems, machine learning, and numerical methods for differential equations.

Research Interests

Stochastic dynamical systems, Artificial Intelligence, Scientific computing, Statistical Modeling, Numerical method for differential equation

Work and Education Experience

March 2024 - Present  Special Professor, School of Mathematics and Physics, China University of Geosciences

March 2021 - March 2024  Research Fellow, Department of Mathematics/I-FIM, National University of Singapore(NUS) (Supervisor: Li Qianxiao)

September 2018 - September 2020 Brown University, Applied Mathematics, Joint Training Program (Supervisor: George Karniadakis)

September 2015 - August 2020  Huazhong University of Science and Technology, Ph.D. in Statistics (Supervisors: Duan Jinqiao, Li Dongfang)

Lead the project

[1]January 2026 to December 2028: Host the National Natural Science Foundation of China Youth Science Fund Project (Class C) 

[2]June 2025 to May 2028: Host the General Project of Chongqing Natural Science Foundation

[3]June 2025 to June 2027: Host the Wuhan Natural Science Foundation Exploration Program (Morning Light Program)

[4]May 2025 to April 2027: Host the Open Project of Guangdong Provincial Key Laboratory

[5]January 2026-December 2028: Host the General Project of  Shenzhen

[6]March 2025 to February 2027: Host the Hubei Provincial Youth Fund Project

[7]September 2016 to September 2019: Hosted the Technology Innovation Fund project at Huazhong University of Science and Technology

Publications

[1]Xiaoli Chen#, Beatrice W. Soh#, Zi-En Ooi, Eleonore Vissol-Gaudin, Haijun Yu, Kostya S. Novoselov*, Kedar Hippalgaonkar*, and Qianxiao Li*. Constructing custom thermodynamics using deep learning. Nature Computational Science, 4(1): 66-85 (2024).

[2]Xiaoli Chen, Phoebus Rosakis*, Zhizhang Wu, and Zhiwen Zhang*. Solving nonconvex energy minimization problems in martensitic phase transitions with a mesh-free deep learning approach. Computer Methods in Applied Mechanics and Engineering 416: 116384 (2023).

[3]Xiaoli Chen*, Liu Yang, Jinqiao Duan, George Em Karniadakis, Solving inverse stochastic problems from discrete particle observations using the Fokker-Planck equation and physics-informed neural networks, SIAM Journal on Scientific Computing, 43(3): B811-B830 (2021).

[4]Jiangyan Liu, Ming Yi, Ting Gao, Xiaoli Chen*. Analysis of influencing factors and the most probable transition pathway in the narrow escape problem for molecular systems based on deep learning method. Chaos, 35(9) (2025).

[5]Jiangyan Liu , jiaqian Zhao, Ming Yi, Jinqiao Duan, Xiaoli Chen*. Data driven discovery of escape phenomena in stochastic systems. Chaos, 35(5) ( 2025).

[6]Xiaoge Guo, Xiaoli Chen, Yan Li,Xiuting Li. Data-driven discovery of slow–fast stochastic differential equations with data binning and sparse bayesian strategy. Stochastics and Dynamics, 2550020 (2025).

[7]Xiaoli Chen*, Jinqiao Duan, George Em Karniadakis. Learning and Meta-Learning of stochastic Advection-Diffusion-Reaction systems from sparse measurements, European Journal of Applied Mathematics, 32(3):397-420 (2021).

[8]Xiaoli Chen, Hui Wang*, Jinqiao Duan. Detecting stochastic governing laws with observation on stationary distributions. Physica D: Nonlinear Phenomena, 448, 133691 (2023).

[9]Jian Ren, Xiaoli Chen*. Identifying stochastic governing equations from data of the most probable transition trajectories. Stochastics and Dynamics, 2340010 (2023).

[10]Xiaoli Chen, Jinqiao Duan*. Nonlocal dynamics for non-Gaussian systems arising in biophysical modeling, Communications on Applied Mathematics and Computation, 2(2): 201-213 (2020).

[11]Xiaoli Chen, Fengyan Wu*, Jinqiao Duan, Jürgen Kurths, Xiaofan Li. Most probable dynamics of a genetic regulatory network under stable Lévy noise, Applied Mathematics and Computation, 348: 425-436 (2019).

[12]Fengyan Wu, Xiaoli Chen*, Yayun Zheng, Jinqiao Duan, Jürgen Kurths, Xiaofan Li. Lévy noise-induced transition and enhanced stability in a gene regulatory network. Chaos, 28(7): 075510 (2018).

[13]Hui Wang, Xiaoli Chen, Jinqiao Duan*. A Stochastic Pitchfork Bifurcation in Most Probable Phase Portraits. International Journal of Bifurcation & Chaos, 28(1): 1850017 (2018).

[14]Xiaoli Chen, Jinqiao Duan, Jianyu Hu*, Dongfang Li. Data-driven method to learn the most probable transition pathway and stochastic differential equation, Physica D: Nonlinear Phenomena, 443, 133559 (2023).

[15]Jianyu Hu, Xiaoli Chen*, Jinqiao Duan. An Onsager-Machlup approach to the most probable transition pathway for a genetic regulatory network, Chaos, 32, 041103 (2022).

[16]Wei Wei, Ting Gao, Xiaoli Chen*, Jinqiao Duan. An optimal control method to compute the most likely transition path for stochastic dynamical systems with jumps, Chaos,32, 051102 (2022).

[17]Xiaoli Chen, Yana Di, Jinqiao Duan, Dongfang Li*. Linearized compact ADI schemes for nonlinear time-fractional Schrödinger equations. Applied Mathematics Letters, 84: 160-167 (2018).

[18]Xiaoli Chen, Jinqiao Duan, Dongfang Li*. A Newton linearized compact finite difference scheme for one class of Sobolev equations. Numerical methods for partial differential equations, 34(3): 1093-1112 (2018).

[19]Boya Zhou, Xiaoli Chen, Dongfang Li*. Nonuniform Alikhanov linearized Galerkin finite element methods for nonlinear time-fractional parabolic equations, Journal of Scientific Computing, 85(2): 1-20 (2020).

[20]Lili Li, Dan Zhao, Mianfu She, Xiaoli Chen*. On high order numerical scheme for the nonlinear fractional differential equations by block-by-block approach, Applied Mathematics and Computation, 425, 127098 (2022).

[21]Rui Cai, Xiaoli Chen*, Jinqiao Duan, Jürgen Kurths, Xiaofan Li. Lévy noise-induced escape in an excitable system. Journal of Statistical Mechanics: Theory and Experiment, 6(6): 063503 (2017).

• 2018.9 -- 2020.8
  Brown University , Mathematics and Applied Mathematics
  Visiting PhD student
• 2015.9 -- 2020.8
  Huazhong University of Science and Technology , Statistics  , Doctoral Degree in Science , Postgraduate (Doctoral)
• 2009.9 -- 2013.6
  武汉纺织大学 , 信息与计算科学  , Bachelor's degree , Undergraduate (Bachelor’s degree)

• 2021.3 -- 2024.8
  National University of Singapore , Department of Mathmatics, Institute for Functional Intelligent Materials (I-FIM) , Research Fellow

• Stochastic dynamical systems、Artificial Intelligence、Scientific Computing、Statistical Modeling、Numerical method for differential equation