Speakers

Yilun Du is an Assistant Professor at Harvard in the Kempner Institute and CS, where he runs the Embodied Minds lab. Yilun received his PhD at MIT EECS, advised by Prof. Leslie Kaelbling, Prof. Tomas Lozano-Perez and Prof. Joshua B. Tenenbaum. Previously, Yilun also obtained his bachelor's degree from MIT, was a research fellow at OpenAI, a senior research scientist at Google Deepmind, and got a gold medal at the International Biology Olympiad. His research focuses on generative models, decision making, robot learning, embodied agents, and the applications of such tools to scientific domains.

Changliu Liu is an associate professor in the Robotics Institute, School of Computer Science, Carnegie Mellon University (CMU), where she leads the Intelligent Control Lab. Prior to joining CMU in Jan 2019, Dr. Liu was a postdoc at Stanford Intelligent Systems Laboratory in 2018. She received her Ph.D. in Engineering together with Master degrees in Engineering and Mathematics from University of California at Berkeley (in 2017, 2014, 2015 respectively) where she worked at the Mechanical Systems & Control Lab. She received her bachelor degrees in Engineering and Economics from Tsinghua University (in 2012). Her research interests lie in the design and verification of human-centered intelligent systems with applications to manufacturing and transportation and on various robot embodiments, including robot arms, mobile robots, legged robots, and humanoid robots. Dr. Liu co-founded Instinct Robotics, a robotics company for intelligent manufacturing. Dr. Liu holds senior membership in IEEE, and membership in ASME and AAAI. She published the book “Designing robot behavior in human-robot interactions” with CRC Press in 2019. She is the co-founder of the International Neural Network Verification Competition launched in 2020. Her work has been recognized by NSF Career Award, Amazon Research Award, Ford URP Award, Advanced Robotics for Manufacturing Champion Award, Young Investigator Award at International Symposium of Flexible Automation, IEEE RAS Early Academic Career Award in Robotics and Automation, IFAC Robotics Outstanding Young Researcher Award, and many best/outstanding paper awards. Her research has been covered by IEEE Spectrum, ATI News, Robtiq Blog, etc, and received support from many government agencies and industrial partners, including NSF, NIST, DARPA, ARM Institute, Boeing, Siemens, Lockheed Martin, etc. She demonstrated their human-robot collaboration system for flexible manufacturing to the US President in 2022. She was a member of the academic council for Grit Venture from 2021 to 2023. She served as the associate editor of Mechatronics from 2023 to 2024 and she is currently the associate editor of ASME Journal of Dynamic Systems, Measurement and Control.

Allen Ren is currently at Physical Intelligence (π) building generalist robot policies, AI models that power any robot to perform any task in the real world. Allen received PhD from Princeton, where he worked with Ani Majumdar on uncertainty quantification of robot learning. During PhD Allen also spent time at Google DeepMind, Toyota Research Institute, NVIDIA, and Stanford. Before that Allen received BS in Mechanical Engineering and MSE in Robotics from Johns Hopkins. Allen built legged robots that self-right, and guitar that senses forces at fingertips.