About me

I’m a second 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

William & Mary

Williamsburg, United States

Ph.D. in Computer Science

2024 - Present

Shanghai Jiao Tong University

Shanghai, China

M.S. in Control Science & Engineering

2021 - 2024

North China Electric Power University

Baoding, China

B.E. in Automation

2017 - 2021

News

  • 2026 — First-author paper “WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems” was accepted to ICML 2026 as a spotlight (top 2.2%).
  • 2026 — First-author paper “WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotics” was accepted to the ICLR 2026 Workshop on World Models: Understanding, Modelling and Scaling.
  • 2026 — Co-author paper “A Generalizable Physics-guided Causal Model for Trajectory Prediction in Autonomous Driving” was accepted to ICRA 2026.
  • 2025 — First-author paper “A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments” was accepted to ICML 2025.
  • 2025 — Co-author paper “Accelerating Neural ODEs: A Variational Formulation-based Approach” was accepted to ICLR 2025.
Show More Show Less
  • 2024 — 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.
  • 2024 — 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.
  • 2024 — Awarded Outstanding Graduate Award, Shanghai Jiao Tong University.
  • 2023 — First-author paper “Temperature State Prediction for Lithium-ion Batteries Based on Improved Physics-Informed Neural Networks” was published in Journal of Energy Storage.

Honors & Awards

  • ICML Gold Reviewer Award (top 25%) — 2026
  • 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
Show More Show Less
  • Third‑Class College Scholarship, North China Electric Power University — 2020
  • Alumni Scholarship, North China Electric Power University — 2019

Services

CoRL (2025), ICML 2026 (Gold Reviewer, top 25%)

ICLR 2026 Workshop on World Models: Understanding, Modelling and Scaling