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My research interests lie in reinforcement learning and robotics. I am particular interested in teaching robots to solve different tasks from human instructions (language, video, etc.). I spent two years as a research student at Cognitive Learning for Vision and Robotics Lab (CLVR), advised by Prof. Joseph J. Lim. I also worked at Horizon Robotics and Duke University. I received my master's degree in Electronic Engineering from University of Southern California (USC). Before that, I did my undergraduate in Fan Gongxiu Honors College at the Beijing University of Technology and majored in Electronic Information Engineering. Google Scholar / Twitter / Linkedin / CV
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Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance
Jesse Zhang, Jiahui Zhang, Karl Pertsch, Ziyi Liu, Xiang Ren, Minsuk Chang, Shao-Hua Sun, Joseph J. Lim CoRL 2023 (Oral) [Arxiv] [Website] [Code] [OpenReview] We propose BOSS, an approach that automatically learns to solve new long-horizon, complex, and meaningful tasks by growing a learned skill library with minimal supervision. |
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SPRINT: Scalable Semantic Policy Pretraining via Language Instruction Relabeling
Jesse Zhang, Karl Pertsch, Jiahui Zhang, Joseph J. Lim ICRA 2024 [Arxiv] [Website] [Code] We propose SPRINT, a scalable approach for pre-training robot policies with a rich repertoire of skills while minimizing human annotation effort. Given a dataset of robot trajectories with an initial set of task instructions for offline pre-training, SPRINT expands the pre-training task set without additional human effort via language-model-based instruction relabeling and cross-trajectory skill chaining. |
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Cross Domain Imitation Learning Through MPC Jiahui Zhang, Haonan Yu, Jesse Zhang, Joseph J. Lim, Wei Xu We present a novel approach leveraging source trajectory and target state-action similarity to replicate the task in the source domain. |
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Principle’s scholarship, Beijing University of Technology. 2018
Outstanding Research Achievement Award, Beijing University of Technology, Fan Gongxiu Honors College. 2017
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Template borrow from Jon Barron's website |