Can we capture natural human interaction with the physical world to train next-generation robotics? In this lunch we will engage with the concepts of using human data to train robots. Just as the Internet evolved into an unintentional data repository for AI, we envision systems that effortlessly capture rich embodied experiences from human activities, without humans’ conscious participation.

Danfei Xu is an Assistant Professor in the School of Interactive Computing and directs the Robot Learning and Reasoning Lab. He is also a researcher at NVIDIA AI. His research focuses on machine learning methods for robotics, particularly in manipulation planning and imitation learning.

ARM is an IMAT Strategic Initiative seeking to connect and engage researchers in materials science, data sciences, and robotics to form partnerships that advance autonomous experimentation and self-driving laboratories.

Registration is required for this event.