CV

Education

• Ph.D. in Computer Science, Department of Computer Science, William & Mary, Sep 2024 – Present
• M.S. in Control Science & Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Sep 2021 – Mar 2024
• B.E. in Automation, School of Control and Computer Engineering, North China Electric Power University, Sep 2017 – Jul 2021

Publications

Temperature state prediction for lithium-ion batteries based on improved physics informed neural networks

Wang, Y., Xiong, C., Wang, Y., Xu, P., Ju, C., Shi, J., ... & Chu, J. (2023). Temperature state prediction for lithium-ion batteries based on improved physics informed neural networks. Journal of Energy Storage, 73, 108863.

Accelerating Neural Differential Equations for Irregularly-Sampled Dynamical Systems Using Variational Formulation

Zhao, H., Wang, Y., Qi, H., Li, J., Sha, L., Zhao, H., & Shao, H. (2024, March). Accelerating Neural Differential Equations for Irregularly-Sampled Dynamical Systems Using Variational Formulation. In ICLR 2024 Workshop on AI4DifferentialEquations In Science..

A Deep Transfer Operator Learning Method for Temperature Field Reconstruction in a Lithium-Ion Battery Pack

Wang, Y., Xiong, C., Ju, C., Yang, G., Chen, Y. W., & Yu, X. (2024). A Deep Transfer Operator Learning Method for Temperature Field Reconstruction in a Lithium-Ion Battery Pack. IEEE Transactions on Industrial Informatics.

Accelerating Neural ODEs: A Variational Formulation-based Approach

Zhao, H., Wang, Y., Qi, H., Huang, Z., Zhao, H., Sha, L., & Shao, H. (2025). Accelerating Neural ODEs A Variational Formulation-based Approach. In The Thirteenth International Conference on Learning Representations.

A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments

Yuchen Wang, Hongjue Zhao, Haohong Lin, Enze Xu, Lifang He, & Huajie Shao. (2025). A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments. Proceedings of the 42nd International Conference on Machine Learning (ICML).

Honors & Awards

• Outstanding Graduate Award, Shanghai Jiao Tong University — 2024
• Graduate Student Merit Scholarship, Shanghai Jiao Tong University — 2023
• Second‑Class Academic Scholarship, Shanghai Jiao Tong University — 2022
• Third‑Class College Scholarship, North China Electric Power University — 2020
• Alumni Scholarship, North China Electric Power University — 2019

Research Experiences

Research Assistant, Department of Computer Science, College of William & Mary

Sep 2024 – Present
Advisor: Prof. Huajie Shao

• First‑author on “A Generalizable Physics‑Enhanced State Space Model for Long‑Term Dynamics Forecasting in Complex Environments,” ICML 2025.
• Co‑author on “Accelerating Neural ODEs: A Variational Formulation–based Approach,” ICLR 2025.
• Co‑author on “A Physics‑Guided Causal Model for Generalizable Zero‑Shot Motion Prediction in Autonomous Driving,” submitted to CoRL 2025.
• Co‑author on “Identifying Invariant Physical Dynamics Across Multiple Environments,” submitted to NeurIPS 2025.

Research Intern, Department of Computer Science, College of William & Mary

Nov 2023 – Jun 2024
Advisor: Prof. Huajie Shao

• Co‑author on “Accelerating Neural Differential Equations for Irregularly‑Sampled Dynamical Systems Using Variational Formulation,” accepted at ICLR 2024 Workshop on AI4DifferentialEquations in Science.

Research Assistant, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University

Sep 2021 – Jan 2024
Advisors: Prof. Changjiang Ju; Prof. Genke Yang

• First‑author on “Temperature State Prediction for Lithium‑ion Batteries Based on Improved Physics‑Informed Neural Networks,” Journal of Energy Storage (IF 8.9).
• First‑author on “A Deep Transfer Operator Learning Method for Temperature Field Reconstruction in a Lithium‑ion Battery Pack,” IEEE Trans. on Industrial Informatics (IF 11.7).
• Designed a production‑planning sub‑algorithm for China’s National Key R&D Program: “Factory Operating System for Intelligent Manufacturing in the Process Industry.”
• Developed algorithms for the Ningbo City–funded project “Dynamic Parameter Detection, Performance Evaluation, and System Safety Technology Development of Lithium‑ion Battery Systems.”
• Completed Master’s thesis: “Research on Key Technologies for Temperature Field Reconstruction in a Lithium‑ion Battery Pack Based on Physics‑informed Machine Learning.”

Research Assistant, School of Control and Computer Engineering, North China Electric Power University

Mar 2020 – Mar 2021
Advisor: Prof. Tongxiang He

• Implemented PID control in SISO and cascade TITO setups for boiler water‐level and feedwater‐flow management.
• Developed DCS configuration diagrams using PAS‑300 software.
• Completed undergraduate thesis: “A Study on Superheated Steam Temperature Control Using State Feedback with Integral Error Based on Simulink.”

Work Experiences

Algorithm Engineer, Battery Management Systems Team

Jun 2022 – Jul 2023
Advisor: Dr. Can Xiong

• Led development of an LSTM‑based algorithm for lithium‑ion battery temperature state estimation.
• Contributed to an Extended Kalman Filter algorithm for state‑of‑charge (SOC) estimation.
• Assisted in designing a Gaussian Process Regression method for state‑of‑health (SOH) prediction.

Intern, Ningbo Industrial Internet Institute

Jun 2021 – Sep 2021
Advisor: Prof. Changjiang Ju

• Developed industrial PLC HMI software in C#, including firmware‐update and file‑operation modules.
• Co‑authored a research report on the hydrogen energy industry.