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Head of Future Robotics Office, Samsung Electronics
Talk title: The Golden Age of Humanoid Robots
Time: 10:00 am, Sep 30
Abstract: We are now entering the golden age of humanoid robots. Until just a few years ago, humanoid robots were regarded primarily as cutting-edge research platforms used to demonstrate advancements in robotics, control, and AI technologies. Today, however, headlines and forecasts abound with predictions that humanoid robots will soon replace human labor in homes and factories. This growing perception is reinforced by the remarkable robots unveiled almost daily by emerging robotics companies in China and major tech firms in the United States. Yet, what often goes unaddressed is a critical question: what specific and practical tasks can these robots actually perform? In fact, there remains a lack of clear standards regarding the form, function, and performance of humanoid robots. In this lecture, we will explore the likely appearance and capabilities of humanoid robots in the near future, focusing on their applications and roles in various domains.
Bio: Professor Jun-Ho Oh (born in 1954) received his B.S. in Mechanical Engineering from Yonsei University in 1977, followed by an M.S. from the same university in 1979. He earned his Ph.D. in Mechanical Engineering from the University of California, Berkeley in 1985. Upon returning to Korea, he joined the faculty of KAIST, where he served until his retirement in 2020. He is currently a Chaired and Emeritus Professor in the Department of Mechanical Engineering at KAIST. Since 2002, he has devoted himself to humanoid robotics, starting with the KHR-1 and KHR-2 models. In 2004, he introduced the HUBO robot and subsequently developed Albert HUBO, HUBO FX-1, HUBO Q, HUBO II, HUBO II+, HUBO T-100, and DRC-HUBO. From 2013, he led a team in the DARPA Robotics Challenge, ultimately winning first place in the finals held in June 2015, along with a $2 million prize. In 2011, he founded Rainbow Robotics. Professor Oh has received numerous awards and honors, including the Order of Science and Technology Merit (Changjo Medal), the Ho-Am Prize in Engineering, the KAIST Grand Prize and Research Prize, the Top 10 Scientists of the Year Award, the Presidential Citation, the 70 Greatest Technologies of Korea Award, the “Most Respected Scientist” Award. He is a member of IEEE, IFAC, the Korean Society of Mechanical Engineers, the Korean Society for Precision Engineering, the Korea Robotics Society, and the Institute of Control, Robotics and Systems. He is also a fellow of the National Academy of Science and Technology of Korea and the National Academy of Engineering of Korea. After retiring from KAIST, he served as CTO at Rainbow Robotics. In January 2025, he was appointed as the head of the Future Robotics Task Force at Samsung Electronics, where he is currently leading related research initiatives.
Professor, University of Texas at Austin
Talk title: Skill learning from video
Time: 10:30 am, Sep 30
Abstract: What would it mean for AI to understand skilled human activity? In augmented reality (AR), a person wearing smart glasses could quickly pick up new skills with a virtual AI coach that provides real-time guidance. In robot learning, a robot watching people in its environment could acquire manipulation skills with less physical experience. Realizing this vision demands significant advances in video understanding, in terms of the degree of detail, viewpoint flexibility, and proficiency assessment. In this talk I’ll present our recent progress tackling these challenges. This includes 4D models to anticipate human activity in long-form video; video-language capabilities for generating fine-grained descriptions of object state changes; and cross-view representations able to bridge the exocentric-egocentric divide---from the view of the teacher to the view of the learner. I’ll also illustrate the impact of these ideas for AI coaching prototypes that guide users through new skills or provide feedback on their physical performance, transforming how-to videos into personalized AI assistants.
Bio: Kristen Grauman is a Professor in the Department of Computer Science at the University of Texas at Austin. Her research focuses on video understanding and embodied perception. Before joining UT-Austin in 2007, she received her Ph.D. at MIT. She is a AAAS Fellow, IEEE Fellow, AAAI Fellow, Sloan Fellow, and recipient of the 2025 Huang Prize and 2013 Computers and Thought Award. She and her collaborators have been recognized with several Best Paper awards in computer vision, including a Marr Prize and a Helmholtz Prize (test of time award). She has served as Associate Editor-in-Chief for PAMI and Program Chair of CVPR 2015, NeurIPS 2018, and ICCV 2023.
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