Huajie Shao

Huajie Shao

I am an Assistant Professor of Computer Science at William & Mary.

I received my Ph.D. from the Computer Science Department at University of Illinois at Urbana Champaign (UIUC), where I was advised by Tarek Abdelzaher (ACM/IEEE Fellow). Before that, I obtained my Master and Bachelor Degrees from Zhejiang Univerisity and Jiangnan University. My research interests focus on Physical AI, World Models, and Interpretable LLM/AI.

/ / / hshao [at] wm (dot) edu

Physical AI Lab (PAI Lab)

At PAI Lab, we work at the intersection of machine learning, control theory, and embodied AI systems, such as robotics, autonomous cars, and drones. Specifically, we focus on Robot World Models and Vision Language Action Models and aim to significantly enhance their reliability, interpretability, and generalizability, particularly through the following three directions.
- Trajectory World Model: Develop a physics-informed trajectory world model for diverse robotics prediction and control.
- Safe Embodied AI: Enable the safety of LLM-based embodied AI systems in the wild.
- Interpretable LLMs/ML: Develop concept-based interpretable LLMs/ML.
Prospective Students: I'm looking for self-motivated students passionate about advancing the frontiers of foundation models and world models for autonomous systems.
- PhD Applicants: If you are interested in working with me, please fill out the Google Form before submitting your application. In addition, please mention my name in your statement of research.
- Intern Students: Please reach out to me directly via email, attaching your CV.

Selected Honors

IEEE/ACM CHASE Best Paper Award, 2025
KDD Best Paper Award, 2024
IEEE/ACM CHASE Best Paper Award, 2024
IEEE/ACM SenSys 2020 Best Paper Award
Fusion 2019 Student Paper Award
UbiComp 2018 Distinguished Paper Award
ICCPS 2017 Best Paper Award