Jiafei Duan - Building Robotics Foundation Model with Reasoning in the loop

Scaling alone won’t unlock general-purpose robotics. Integrating reasoning directly into robot learning (spatial, temporal, and failure-based) so robots can learn more from limited data and continuously self-improve is the path forward. Jiafei Duan is a fourth & final year PhD student in Robotics and AI at the Paul G. Allen School of Computer Science & Engineering, University of Washington, co-advised by Ranjay Krishna and Dieter Fox . His research centers on robot learning, embodied AI, and building large-scale robotics foundation models. His work has received Best Paper, Spotlight, and Oral recognitions at venues including ICLR, UR, and RSS, and has been featured in MIT Technology Review, GeekWire, VentureBeat, and Business Wire. Jiafei is also a Graduate Student Researcher at the Allen Institute for AI (AI2) and has previously worked as a Research Scientist Intern at NVIDIA. He earned his B.Eng. in Electrical and Electronic Engineering with Highest Distinction from Nanyang Technological University (NTU), Singapore. This session is brought to you by the Cohere Labs Open Science Community - a space where ML researchers, engineers, linguists, social scientists, and lifelong learners connect and collaborate with each other. We'd like to extend a special thank you to Nahid Alam and Cole Harrison, Leads of our Embodied AI group for their dedication in organizing this event. If you’re interested in sharing your work, we welcome you to join us! Simply fill out the form at https://forms.gle/ALND9i6KouEEpCnz6 to express your interest in becoming a speaker. Join the Cohere Labs Open Science Community to see a full list of upcoming events (https://tinyurl.com/CohereLabsCommunityApp).