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Zhengyi Luo is a Research Scientist at NVIDIA GEAR Lab. His research lies at the intersection of robotics, vision, and learning, including humanoid control, humanoid–object interaction, and egocentric perception. He is the lead author of SONIC, a large-scale motion-tracking foundation model for natural humanoid whole-body control.
Taku Komura is a Professor at the University of Hong Kong. His research focuses on data-driven and physically-based character animation, crowd simulation, 3D modelling, and robotics. Recently, his main research interests have been on physically-based animation and the application of machine learning techniques for animation synthesis, including human–scene interaction.
Kwan-Yee Lin is a Research Fellow in the EECS Department at UMich, working with Prof. Stella X. Yu. She received her Ph.D. from Peking University, where she was awarded the Presidential Scholarship, the university’s highest graduate-level honor for academic and research excellence. She previously was a postdoctoral researcher at The Chinese University of Hong Kong, and spent several years in industry as Director of an R&D department, leading the development of over 30 mass-produced systems used by major automotive manufacturers worldwide.
Umar Iqbal is a Senior Research Manager at NVIDIA Research, leading the Data-Driven AI for Robotics (DAIR) team. The team investigates how robots can learn directly from human data, such as videos, motion capture, and large-scale demonstrations, to acquire skills that generalise across tasks, embodiments, and environments.
Gerard Pons-Moll is Professor at the University of Tübingen and core faculty at the Tübingen AI Centre. His research lies at the intersection of computer vision, computer graphics, and machine learning, with special focus on analysing people in videos and creating virtual human models. His recent work spans human-object interaction modelling, human-scene interaction modelling and 3D human reconstruction.
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