William Chen
verityw [AT] berkeley [DOT] edu | LinkedIn | GitHub | Twitter
I am a Computer Science PhD candidate at UC Berkeley's RAIL Lab,
advised by Dr. Sergey Levine.
My research focuses on Robots That Reason.
Previously, I received a M.Eng. in Electrical Engineering and Computer Science from MIT, after having finished
my B.S. in the same department. I conducted my thesis work in the SPARK
Lab, where I investigated the use of language models to improve robots' abilities to understand their
environments under Dr. Luca Carlone and Jacob Andreas.
I was also a robotics intern at NASA's Jet Propulsion Laboratory.
Publications
FRS: Improving Robotic Generalist Policies via Flow Reversal Steering
Andy Tang, William Chen, Andrew Wagenmaker, Chelsea Finn, Sergey Levine
Paper · Website
This work was accepted at the RSS 2026's Diffusion for Robot Learning and 3rd Workshop on Semantic Reasoning and Goal Understanding in Robotics workshops, where it won Best Student Paper at both!
Steerable Vision-Language-Action Policies for Embodied Reasoning and Hierarchical Control
William Chen, Jagdeep Bhatia, Catherine Glossop, Nikhil Mathihalli, Ria Doshi, Andy Tang, Danny
Driess, Karl Pertsch, Sergey
Levine
Paper · Website · Code
This work was accepted at RSS 2026.
ECoT-Lite: Training Strategies for Efficient Embodied Reasoning
William Chen, Suneel Belkhale, Suvir Mirchandani, Oier Mees, Danny Driess, Karl Pertsch, Sergey
Levine
Paper · Website
This work was accepted at CoRL 2025, where it was selected as an Oral Presentation.
ECoT: Robotic Control via Embodied Chain-of-Thought Reasoning
Michał Zawalski, William Chen, Karl Pertsch, Oier Mees, Chelsea Finn, Sergey Levine
Paper · Website ·
Code · Models · Colab
This work was accepted at CoRL 2024. It was also featured in the 2024 State of AI report (slide 77). This work was co-first authored by me and Michał Zawalski.
PR2L: Vision-Language Models Provide Promptable Representations for Reinforcement Learning
William Chen, Oier Mees, Aviral Kumar, Sergey Levine
Paper · Website
This work was accepted to TMLR March 2025.
LITEN: Learning Affordances at Inference-Time for Vision-Language-Action Models
Ameesh Shah, William Chen, Adwait Godbole, Federico Mora, Sanjit A. Seshia, Sergey
Levine
Paper · Website
This work was accepted at ICRA 2026.
Indoor and Outdoor 3D Scene Graph Generation via Language-Enabled Spatial Ontologies
Jared Strader, Nathan Hughes, William Chen, Alberto Speranzon, Luca Carlone
Paper
LaMPP: Language Models as Probabilistic Priors for Perception and Action
Belinda Z. Li, William Chen, Pratyusha Sharma, Jacob Andreas
Paper
Organizing and Service
Workshops
- Invited Speaker and Panelist at the Reinforcement Learning for Vision-Language-Action Models Workshop (RL4VLA) at RSS 2026
- Panel Organizer for the Evaluation and Deployment Workshop at CoRL 2025
- Lead Organizer for the Workshop on Learned Robot Representations (RoboReps) at RSS 2025
- Panelist at the Third Workshop on Language and Robot Learning at CoRL 2024
Talks
- April 2026: Invited talk at UW Wisconsin's RT2 Lab
Education
University of California, Berkeley
Ph.D. - Computer Science (June 2023 - Present)
Supported by the NDSEG Fellowship.
Teaching Assistant for Deep Learning (Fall 2024).
Massachusetts Institute of Technology
M.Eng. - Electrical Engineering and Computer Science (Feb 2022 - June 2023)
Teaching Assistant for Natural Language Processing (Fall 2022).
Teaching Assistant for Robotics: Science and Systems (Spring 2021, 2022).
B.S. - Electrical Engineering and Computer Science (Aug 2019 - Feb 2022)
Bronx High School of Science
High School (Sept 2015 - June 2019)