Benjamin Eysenbach
About
Benjamin Eysenbach is an Assistant Professor of Computer Science at Princeton University, where he leads the Princeton Reinforcement Learning Lab. His research focuses on designing reinforcement learning (RL) algorithms that learn intelligent behaviors through self-supervised methods, eliminating the need for explicit rewards or human supervision. Eysenbach's work emphasizes simplicity, scalability, and robustness, contributing to advancements in goal-conditioned RL and contrastive learning techniques. He earned his Ph.D. in Machine Learning from Carnegie Mellon University, advised by Ruslan Salakhutdinov and Sergey Levine, and held research positions at Google Brain. His academic journey began with undergraduate studies in mathematics at MIT. At Princeton, Eysenbach teaches courses on reinforcement learning and probabilistic inference, and his lab's research has been featured in leading conferences such as ICLR and NeurIPS. Read more