3rd Offline RL Workshop: Offline RL as a "Launchpad"

Neural Information Processing Systems (NeurIPS)

December 2, 2022

@OfflineRL ยท #OFFLINERL

Invited Speakers

Dorsa Sadigh is an assistant professor at Stanford University. My research interests lie at the intersection of robotics, machine learning, and control theory. Specifically, her group is interested in developing efficient algorithms for safe, reliable, and adaptive human-robot and generally multi-agent interactions.
Akshay Krishnamurthy is a principal researcher at Microsoft Research NYC. Previously, he spent two years as an assistant professor in the College of Information and Computer Sciences at the University of Massachusetts, Amherst. His research interests are in machine learning and statistics and he is most excited about interactive learning.
Tony Jebara is VP of engineering for personalization at Spotify. He also heads the company-wide machine learning strategy. Previously, he was a professor at Columbia university.
Alex Kendall is the co-founder and CEO of Wayve, the London-based company pioneering AI technology to enable autonomous vehicles to drive in complex, never-seen-before environments. Before founding Wayve, Alex was a research fellow at Cambridge University where he earned his Ph.D. in Computer Vision and Robotics. He has been selected on the Royal Academy of Engineering's SME Leaders Programme and named on the Forbes 30 Under 30 innovators list.
Martin Riedmiller is a research scientist and former professor for machine learning and now a team lead at DeepMind. His core scientific interest are intelligent machines, that are able to autonomously learn new things from scratch. He is particular interested in neural networks and their ability to store and generalize information.
Taylor Killian is a PhD student at MIT who focuses on using reinforcement Learning to assist clinical decision making. He works in the fields of reinforcement learning, machine learning, and causal inference. He has long been interested in decision making and the mechanisms by which humans summarize and reason about the world. In my work, I aim to develop models and algorithms that enable actors (whether human or not) to efficiently make decisions in the face of various forms of uncertainty.
Invited speakers would be part of a lively panel, which would be livestreamed during the workshop.