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
Ph.D. in Computer Science
Williamsburg, United States
Shanghai Jiao Tong University
M.S. in Control Science & Engineering
Shanghai, China
North China Electric Power University
B.E. in Automation
Baoding, China
News
2026Co-author paper “Lens: A Knowledge-Guided Foundation Model for Network Traffic” was accepted to Transactions on Machine Learning Research (TMLR).
2026First-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%).
2026First-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.
2026Co-author paper “A Generalizable Physics-guided Causal Model for Trajectory Prediction in Autonomous Driving” was accepted to ICRA 2026.
2025First-author paper “A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments” was accepted to ICML 2025.
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2025Co-author paper “Accelerating Neural ODEs: A Variational Formulation-based Approach” was accepted to ICLR 2025.
2024First-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.
2024Co-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.
2024Awarded Outstanding Graduate Award, Shanghai Jiao Tong University.
2023First-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
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