By Benjamin Van Roy (Stanford University)
Talk Abstract: Reinforcement learning is poised to play a major role in emerging generative AI systems that rely on learning from human feedback after pretraining enormous models on massive data sets. I will discuss opportunities in this area.
Speaker Bio: Benjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His current research focuses on reinforcement learning. Beyond academia, he leads a DeepMind Research team in Mountain View. He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edited the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization. He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT, where his doctoral research was advised by John N. Tstitsiklis. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master’s Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, the Management Science and Engineering Department’s Graduate Teaching Award, and the INFORMS Lanchester Prize.