Shane Legg is the Co-Founder & Chief Scientist at DeepMind. His main research interests are in artificial intelligence, both theory and practice. In particular, he is interested in measures of intelligence for machines, neural networks, artificial evolution, reinforcement learning and the theory of learning.

Joelle Pineau is an Associate Professor and William Dawson Scholar at the School of Computer Science at McGill University, where she co-directs the Reasoning and Learning Lab. She is a core academic member of Mila and a Canada CIFAR AI chairholder. She is also co-Managing Director of Facebook AI Research. Dr. Pineau's research focuses on developing new models and algorithms for planning and learning in complex partially-observable domains. She also works on applying these algorithms to complex problems in robotics, health care, games and conversational agents.

Pierre-Yves Oudeyer is research director (DR1) at Inria, heading the Flowers team at Inria Bordeaux Sud-Ouest. His research focuses on lifelong autonomous learning, and the self-organization of behavioural, cognitive and language structures, at the frontiers of artificial intelligence, machine learning, and cognitive sciences. He uses machines as tools to understand better how children learn and develop, and studies how one can build machines that learn autonomously like children, within the new field of developmental artificial intelligence.

Katja Hofmann is a Senior Principal Researcher within the Machine Intelligence theme at Microsoft Research Cambridge. She leads a team that focuses on Deep Reinforcement Learning for Games, with a mission to advance the state of the art in reinforcement learning, driven by current and future applications in video games. Her team shares the belief that games will drive a transformation of how we interact with AI technology. Her long-term goal is to develop AI systems that learn to collaborate with people, to empower their users and help solve complex real-world problems.

Daniel Tanis is a Research Scientist at DeepMind. He completed a Ph. D. at the University of Cambridge and previously worked at Google. His current research focuses on understanding how training environments can be used to improve the performance of reinforcement learning agents.

Benjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His research focuses on the design, analysis, and application of reinforcement learning algorithms. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.

Warren Powell is a professor in the Department of Operations Research and Financial Engineering at Princeton University where he has taught since 1981. His interests focus on optimization under uncertainty, broadly defined, drawing on applications in energy, transportation, health, business analytics and the sciences. He has written books on Approximate Dynamic Programming and Optimal Learning, and is working on a new book that creates a unified framework spanning all the major subfields of stochastic optimization. He is an Informs Fellow, has won the Daniel Wagner prize and was twice an Edelman finalist.

Amy Zhang is a postdoctoral scholar at UC Berkeley and a research scientist at Facebook AI Research. Her research focuses on state abstractions, model-based reinforcement learning, representation learning, and generalization in RL. She completed her PhD at McGill University and Mila - Quebec AI Institute, co-supervised by Joelle Pineau and Doina Precup. She also holds an M.Eng. in EECS and dual B.Sci. degrees in Mathematics and EECS from MIT.

Tom Griffiths is a professor of psychology and computer science at Princeton, where he directs the Computational Cognitive Science Lab. His research focuses on developing mathematical models of higher-level cognition and understanding the formal principles that underlie our ability to solve the computational problems we face in everyday life. He has published scientific papers on topics ranging from cognitive psychology to cultural evolution and has received awards from the National Academy of Sciences, the Sloan Foundation, the American Psychological Association, and the Psychonomic Society, among others.

Michiel van de Panne is a professor in the Computer Science department at University of British Columbia. His research interests span reinforcement learning, control, physics-based simulation of human and animal movement, robotics, computer animation, and computer graphics.

Jeff Clune is a Research Team Leader at OpenAI and an Associate Professor of Computer Science at the University of British Columbia. Previously, Jeff was a Senior Research Manager and founding member of Uber AI Labs, which was formed after Uber acquired our startup. Prior to Uber, Jeff was the Loy and Edith Harris Associate Professor in Computer Science at the University of Wyoming.