Chen Sun

Chen Sun is an Assistant Professor of Computer Science at Brown University and a part-time Staff Research Scientist at Google DeepMind. His research bridges computer vision, machine learning, and artificial intelligence, focusing on multimodal representation learning, visual commonsense, and controllable video generation. He directs the PALM🌴 research lab, which explores scalable models for robotic planning, video understanding, and human activity recognition.

Chen Sun earned a Ph.D. in Computer Science from the University of Southern California (2016), advised by Professor Ram Nevatia, and a Bachelor of Science in Computer Science from Tsinghua University (2011). His lab's work has been supported by Adobe, Honda, Meta, NASA, and Samsung, and he is affiliated with the NSF AI Research Institute on Interaction for AI Assistants.

His research spans multimodal transformers, embodied agents, and physics-informed video generation. Key trends include

• Learning from unlabeled videos for human activity recognition
• Developing controllable generation techniques using motion trajectories and physics-based signals
• Advancing scalable frameworks for video-language tasks

Scientific awards include the Brown University Richard B. Salomon Faculty Research Award and Samsung Global Research Outreach Award. He has served as Workshop Chair (CVPR 2025), Action Editor (TMLR), and Area Chair for top conferences like ICLR, CVPR, and NeurIPS.

Chen Sun mentors a dynamic team including Ph.D. students

• Apoorv Khandelwal (Presidential Fellow)
• Calvin Luo (Research Mobility Fellow)
• Nate Gillman (Math Department)
• Shijie Wang
• Tian Yun (co-advised with Ellie Pavlick)
• Yuan Zang
• Zilai Zeng
• Zitian Tang

and alumni now pursuing Ph.D. programs at Princeton, Cornell, UBC, and UNC.

His teaching portfolio includes graduate-level courses on Deep Learning (CSCI 2470), Advanced Topics in Deep Learning (CSCI 2952N), and a short course on Multimodal Transformers at ICASSP 2022 and AAAI 2023.