Jason Chen

I am a fourth year undergraduate student at the University of Southern California working with Daniel Seita and Gaurav S. Sukhatme. I am incredibly grateful to be collaborating with Yue Wang. I'm majoring in Computer Science.

My current research focuses on a data-driven approach to improving policy generalization and robustness by generating synthetic data using video and image generation models for deployment in VLA and imitation learning policies.

I am currently also getting an accelerated master's degree in Computer Science at USC.

Looking for PhD programs starting in Fall 2027!

profile photo

Research

* indicates equal contribution. † indicates equal advising.

CRAFT: Video Diffusion for Bimanual Robot Data Generation

Jason Chen, I-Chun (Arthur) Liu, Gaurav S. Sukhatme, Daniel Seita

CRAFT generates diverse, photorealistic robot training data from simulation using video diffusion.

In Submission, 2026

ROPA: Synthetic Robot Pose Generation for RGB-D Bimanual Data Augmentation

ROPA: Synthetic Robot Pose Generation for RGB-D Bimanual Data Augmentation

Jason Chen, I-Chun (Arthur) Liu, Gaurav S. Sukhatme, Daniel Seita

ROPA is a data augmentation method for bimanual imitation learning that generates 3rd person robot poses.

International Conference on Robotics and Automation (ICRA), 2026

D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation

D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation

I-Chun (Arthur) Liu, Jason Chen, Gaurav S. Sukhatme, Daniel Seita

D-CODA is a method for offline data augmentation tailored to eye-in-hand bimanual imitation learning.

Conference on Robot Learning (CoRL), 2025





Awards


Services

Inspired by the template here.