Glen is an Assistant Professor at the Université de Montréal. His research has focused on solving sequential decision-making problems (planning) for real-world autonomous learning systems (robots).
Liam is an Assistant Professor at the Université de Montréal. His research lab is focussed on building representations of the world (such as for simultaneous localization and mapping), modeling of uncertainty, and building better workflows to teach robotic agents new tasks (such as through simulation or demonstration).
Maani is an assistant professor at the University of Michigan. He is interested in applied mathematics, robotic perception, machine learning, and planning under uncertainty with applications in robotics and autonomous systems.
Animesh is an Assistant Professor of Computer Science at University of Toronto. His research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments.
Mayank is currently a PhD student at ETH Zurich advised by Marco Hutter, and a Research Scientist at NVIDIA Research.
Hsiu-Chin is an Assistant Professor at McGill is interested in the fields of robotics and machine learning for motor control. She’s interested in enabling robots to assist humans in our everyday activities.
Nikita Rudin is a robotics researcher at NVIDIA and a PhD Student at the Robotic Systems Lab, ETH Zurich. Before that Nikita completed a Bachelor in Microengineering at EPFL and a Master in Robotics, Systems and Control at ETH Zurich. His research focuses on Reinforcement Learning for locomotion. More Specifically, he aims to push the capabilities of real-world legged robots by training them to be more agile in complex environments with learned locomotion, navigation and perception.
David is a Deep Learning Research Scientist. Currently a PhD Student at Robotic Systems Lab, ETH Zurich & Research Scientist at Nvidia.
Laura is a Senior Research Engineer at Google Robotics, where she works on a mix of research and engineering. Her research interests include reinforcement learning, environment design, and evolutionary algorithms. For the past 4.5 years, her focus has been on robotic table tennis, although occasionally, she works in other areas. Laura has a B.A. in Politics, Philosophy, and Economics from the University of Oxford and an M.S. in Computer Science from New York University. She also co-wrote a textbook called Foundation of Deep Reinforcement Learning and an open-source library for reproducible deep reinforcement learning.