I’m a first year phd student from William & Mary, advised by Professor Huajie Shao. My current research interest focuses on developing physics‑informed machine learning methods to build generalizable world models, with applications spanning robotics, autonomous driving, and power systems.

You can find my CV here: Yuchen Wang’s Curriculum Vitae.

Education

• Ph.d. in Computer Science (2024-present), William & Mary, Williamsburg, United States.
• M.S. in Control Science & Engineering (2024), Shanghai Jiao Tong University, Shanghai, China.
• B.E. in Automation (2021), North China Electric Power University, Baoding, China.

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

News

• First‑author paper “A Generalizable Physics‑Enhanced State Space Model for Long‑Term Dynamics Forecasting in Complex Environments” was accepted to ICML 2025.
• Co‑author paper “Accelerating Neural ODEs: A Variational Formulation‑based Approach” was accepted to ICLR 2025.
• First‑author paper “A Deep Transfer Operator Learning Method for Temperature Field Reconstruction in a Lithium‑Ion Battery Pack” was published in IEEE Transactions on Industrial Informatics.
• Co‑author paper “Accelerating Neural Differential Equations for Irregularly‑Sampled Dynamical Systems Using Variational Formulation” was presented at the ICLR 2024 Workshop on AI4DifferentialEquations In Science.
• Awarded Outstanding Graduate Award, Shanghai Jiao Tong University — 2024.
• First‑author paper “Temperature State Prediction for Lithium‑ion Batteries Based on Improved Physics‑Informed Neural Networks” was published in Journal of Energy Storage.

Contact Information

• Phone: +1 757-332-8055
• Email: ywang142@wm.edu