I got my bachelor's and master's degrees in Control Science and Engineering from Beijing University of Posts and Telecommunications (BUPT) in 2020 and 2023, respectively. I am currently a first-year joint Ph.D. student in Computer Science and Technology at Zhejiang University and Westlake University (Machine Intelligence Lab, MiLAB), advised by Prof. Donglin Wang.
My current research interests include Embodied Artificial Intelligence, Foundation Models, Reinforcement Learning, and Robotics.
Specifically, I am interested in:
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Foundation Models for Robotics: developing efficient and effective foundation models for robotics, including multi-modal large language models and vision-language-action models to enhance the perception and decision-making capabilities of robots.
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Scalable Reinforcement Learning Algorithms: developing reinforcement learning algorithms that can effectively manage large-scale data and model capacity for robotic control. This includes methods such as offline reinforcement learning, imitation learning, and more, with the goal of enabling robots to acquire scalable and generalizable skills.
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Motion Planning and Control for Legged Robots: developing motion planning and control algorithms for legged robots, including bipedal and quadruped robots, to enable them to perform complex tasks in real-world environments.
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[July 4, 2024] Two papers (PiTe and QUAR-VLA) have been accepted for ECCV 2024!
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[June 30, 2024] One paper (GeRM) has been accepted for IROS 2024!
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[May 14, 2024] One paper (RL2AC) has been accepted for RSS 2024!
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[March 22, 2024] A new paper about Cobra, an efficient multi-modal large language model, was released. Project page has been available. The paper has been featured by Hugging Face Daily Papers! Demo has been available!
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[March 20, 2024] A new paper about GeRM, a generalist robotic model with the mixture-of-experts architecture and RL training method for quadruped robot, was released. Project page has been available. Video has been available!
zhaohan34[at]westlake.edu.cn