Aravind Rajeswaran is a Research Scientist at FAIR (Meta) working on reinforcement learning and world models to enable goal-directed AI agents. Some of his most notable projects include DAPG, Decision Transformers, R3M, and OpenEQA. He earned his PhD from the University of Washington under Profs. Sham Kakade and Emo Todorov, where he worked on algorithmic foundations of reinforcement learning and meta learning. He is a recipient of multiple honors, including a J.P. Morgan PhD Fellowship for AI, a best paper awards at IEEE SIMPAR (2018), and a best undergraduate thesis award from IIT Madras.