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Yuke Zhu is an Associate Professor in the Department of Computer Science at the University of Texas at Austin and the director of the Robot Perception and Learning (RPL) Lab. He is also a Director and Distinguished Research Scientist at NVIDIA Research, where He co-leads the Generalist Embodied Agent Research (GEAR) group. His goal is to build algorithms and systems for autonomous robots and embodied agents that reason about and interact with the real world. His research lies at the intersection of robotics, machine learning, and computer vision. He focuses on developing methods and principles of perception and decision-making to realize general-purpose robot autonomy in the wild.
Talk: "Building Self-Improving and Continual Learning VLAs"
Ziwei Wang is currently an assistant professor in School of Electrical and Electronic Engineering, Nanyang Technological University and the director of Perception and embodied INtElligence (PINE) Lab. Before joining NTU, he was a postdoc fellow in Robotics Institute, Carnegie Mellon University, with Prof. Changliu Liu. He received the Ph.D and the B.S degrees from the Department of Automation, Tsinghua University in 2023 and the Department of Physics, Tsinghua University in 2018 respectively. His research goal is to design foundation models (FMs) for robotic manipulation. He has published over 50 scientific papers in TPAMI, IJCV, RAL, CVPR, ICCV, ECCV, NeurIPS, CoRL, IROS and ICRA. He serves as a regular reviewer member for a variety of conferences and journals.
Talk: "Accelerating Sample-Efficient Reinforcement Learning for Real-World Robotic Manipulation"
Chao Yu（于超 received her Ph.D. from the Department of Electronic Engineering at Tsinghua University in 2023. She is currently an Assistant Professor (Distinguished Research Fellow) at the Embodied Decision Intelligence Lab (EDI Lab) at Tsinghua Shenzhen International Graduate School (SIGS). She also serves as the chairman of the Tsinghua Shenzhen International Graduate School - AgiBot Joint Research Center for Embodied Cognition and Decision Systems (JCES) 清华-智元联合研究中⼼主任. She has been selected for the Youth Talent Support Program of the Chinese Institute of Electronics. Her research has long focused on reinforcement learning–based decision intelligence.
Talk: "TBD"
Will is a third year PhD student at UC Berkeley, advised by Sergey Levine. His research focuses on Robots that Reason -- how embodied reasoning can be leveraged to make robotic foundation models more generalizable, steerable, and amenable to improvement. Prior to Berkeley, he received his BS and MEng at MIT, advised by Luca Carlone and Jacob Andreas. His research there focused on how to apply semantic knowledge in language models for robotic scene understanding. He was also a robotics intern at NASA's Jet Propulsion Laboratory.
Talk: "Steerable VLAs that Reason"
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