Panels

We plan to organize 1 panel discussion on the topic mentioned below.

Challenges & Open Problems in Reusing Prior Computation

Moderator: Rishabh Agarwal, Ted Xiao, Yanchao Sun

Panelists

	Jeff Clune - UBC Jeff Clune is an Associate Professor of computer science at the University of British Columbia and Canada CIFAR AI Chair at the Vector Institute. Jeff focuses on deep learning, including deep reinforcement learning. Previously he was a research manager at OpenAI, a Senior Research Manager and founding member of Uber AI Labs (formed after Uber acquired a startup he helped lead), the Harris Associate Professor of Computer Science at the University of Wyoming, and a Research Scientist at Cornell University.
	Marc G. Bellemare - Google Research, Brain Team Marc leads the RL efforts of the Google Brain team in Montréal, Canada. He is also a core industry member at Mila, where he advises graduate students. He obtained his PhD from the University of Alberta in Canada, proposing the use of Atari 2600 video games to benchmark progress in reinforcement learning research.
	Joseph Lim - Korea Advanced Institute of Science and Technology (KAIST) Joseph is an Associate Professor in the Kim Jaechul School of Artificial Intelligence at KAIST, where he leads the Cognitive Learning for Vision and Robotics lab .
	Jim (Linxi) Fan - Nvidia AI Jim is a research scientist at NVIDIA AI. His primary focus is to develop generally capable autonomous agents. To tackle this grand challenge, my research efforts span foundation models, policy learning, robotics, multimodal learning, and large-scale systems.
	Anna Goldie - Anthropic / Stanford University Anna is currently a researcher at Anthropic. Previously, she was a Staff Research Scientist at Google Brain and co-founder/lead of the ML for Systems team, where her research focus was on developing deep RL approaches to problems in computer systems, particularly chip design.
	Furong Huang - University of Maryland Dr. Furong Huang is an Assistant Professor of the Department of Computer Science at the University of Maryland. Her research focuses on machine learning, high-dimensional statistics, non-convex optimization, spectral methods, reinforcement learning and deep learning theory.
	Avishkar Bhoopchand - DeepMind Avishkar is currently a Research Engineer at Google DeepMind. He is part of the Deep Learning Indaba team and contributed to the advancement of Machine Learning in Africa.