Jalaj Bhandari

Jalaj Bhandari, PhD, is a postdoctoral researcher at Meta's Applied Reinforcement Learning team since January 2023, focusing on reinforcement learning and contributing to the development of the Pearl library. Prior experience includes a postdoctoral fellowship with Prof. Doina Precup at Mila, working on multi-task reinforcement learning, and a research fellowship at the Simons Institute, where research centered on state aggregation methods in reinforcement learning. Jalaj's industry experience includes an applied science internship at Amazon, optimizing ad-allocation algorithms, and research internships at Invitae and Adobe, where contributions involved developing sampling approaches for genetic testing recommendations and a reinforcement learning framework for personalized marketing, respectively. Jalaj holds a PhD in Reinforcement Learning and Machine Learning from Columbia University and a Bachelor's degree in Operations Research from the Indian Institute of Technology, Delhi.