Keynotes

Xinlei Chen is a research scientist at FAIR, Meta AI. His research interests are in computer vision and machine learning. He got his Ph.D. from Carnegie Mellon University in 2018, and a B.S. from Zhejiang University in 2012. He is a recipient of CVPR Best Paper Honorable Mention and ICML Outstanding Paper Honorable Mention awards in 2021, and two CVPR 2022 Best Paper finalists, all of which on self-supervised representation learning.

Jason (Yao) Lu is a principal research scientist at Nvidia, leading VILA project. Prior to that, Yao was a staff research manager at Google Deepmind where he co-led the development of "SayCan", "RT-1" and "RT-2". His research focuses on reinforcement learning, imitation learning, and VLM. His work has received best paper awards at CoRL, ICRA, etc. and featured by New York Times, Washington Post, Forbes, Reuters, TechCrunch, The WIRED, etc. He received his PhD. at University of California, San Diego.

Ishan Misra is a Research Scientist in Meta AI. His research interest is in using automatic supervision at scale to build machine learning models. Ishan got his PhD from the Robotics Institute at Carnegie Mellon University where he also received the SCS Distinguished Dissertation award (Runner Up). For his work on self-supervised learning, he was featured in the  MIT Tech Review’s 35 innovators under 35 list. You can hear him on Lex Fridman’s podcast for a fun overview of his work.

Ranjay Krishna is an Assistant Professor at the Paul G. Allen School of Computer Science & Engineering, focusing on computer vision and human-computer interaction. His work has earned best paper and oral awards at CVPR, ACL, CSCW, NeurIPS, UIST, and ECCV, and has been featured in Science, Forbes, the Wall Street Journal, and PBS NOVA. Supported by Google, Amazon, Cisco, Toyota, NSF, ONR, and Yahoo, he holds a bachelor's in Electrical & Computer Engineering and Computer Science from Cornell, and a master’s and Ph.D. in Computer Science from Stanford.