people
HKUST (GZ) PEAK-Lab is a research group dedicated to embodied AI and autonomous systems. Our mission is to bring AI into the physical open world by enabling machines to understand general motion, perceive 3D scenes, and actively navigate and interact with their surroundings.
Changhao Chen is an assistant professor at the Intelligent Transportation Thrust and Artificial Intelligence Thrust, HKUST (GZ). He received Ph.D. in Computer Science from University of Oxford. His research interests lie in embodied AI and autonomous systems, particularly the challenges of open-world perception and navigation.
Changqing Zhou is an incoming Ph.D. student at HKUST-GZ, where he will be advised by Prof. Changhao CHEN. He holds an M.S. in Artificial Intelligence from NTU and a B.S. in Mechanical Engineering from SJTU. His research interests focus on 3D vision and scene understanding. He aims to develop embodied agents capable of perceiving and interacting with the real world, with the ultimate goal of delivering tangible benefits to everyday life.
Zeyu Jiang is an upcoming PhD student at HKUST-GZ, supervised by Prof. Changhao Chen. Previously, he obtained his master’s degree at NTU and bachelor’s degree at BIT. His research interests focus on embodied perception based on visual SLAM. He is interested in robotics and committed to joining the development of embodied AI into the physical world.
Qunchao Jin is a Research Assistant at Peak Lab, where he focuses on foundation model-based embodied navigation. Previously, he worked as a Computer Vision Researcher at Lenovo Research, developing robotic inspection systems. He holds a Master’s degree from East China Normal University, with research in medical image analysis. Driven by a broad interest in AI applications across industries, Qunchao aims to bridge advanced research with practical solutions to real-world challenges.
Dehan Shen is a research assistant working with Prof. Changhao Chen. He graduated from the University of Sheffield with a Master’s degree in Robotics and from Shanghai University with a Bachelor’s degree in Electronic Information Engineering. His research interests include learning-based inertial odometry and proprioceptive intelligence.
Lingjie Zhang is a research assistant at PEAK-LAB, HKUST(GZ), advised by Prof. Changhao Chen, and a master’s student in Automotive Engineering at the Technical University of Munich. He is interested in embodied navigation, particularly in learning-based motion planning and control.
Yufei Zhang is a research assistant in PEAK lab working with Prof. Chen Changhao. He received his undergraduate degree from the School of Information Science and Engineering of Fudan University and his postgraduate degree from Nanyang Technological University. His current research interests include multimodal continuous learning and embodied intelligence.
Chenyang Li is a Research Assistant at HKUST(GZ), working in the PEAK Lab with Prof. Changhao Chen. He is also pursuing a Master of Science in Data Science at Nanyang Technological University. He is interested in embodied AI, robot perception and decision-making, and adversarial robustness in deep and reinforcement learning.
Renmin Cheng is a research assistant at HKUST(GZ) working with Prof.Changhao Chen. Before that, He works as RD at Baidu. He graduated from Xidian Uninersity with a Master’s degree in Engineering , and from the Heilongjiang University with an undergraduate degree in Engineering.
Zihan Zhang is a Research Assistant Intern at HKUST(GZ) Peak Lab, under the supervision of Prof. Changhao Chen. He is currently a second-year master student in Johns Hopkins University. He is currently working on lightweight Transformer models for matching neural networks. His research interests lie on Efficient Model Inference, Artificial Intelligence for Generative Contents and Artificial Intelligence for Healthcare.
Jialong Liu Research Assistant Working with Prof. Changhao Chen at HKUST (GZ). Graduated from Guangdong University of Technology. Has participated in multiple robotic competitive events. Interested in integrating algorithms and hardware for robot control.