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I am a research scientist at FAIR, working with the Embodied AI and RL teams. I also collaborate with and advise students in Prof. Abhinav Gupta's lab in FAIR/CMU and Prof. Pieter Abbeel's lab in UC Berkeley. I work on algorithmic foundations of deep learning and reinforcement learning. My recent focus areas include learning from passive or offline experience, representation learning, and learning generative models for decision making. I use these algorithmic tools in applications like robotics, personalized recommendation systems, and character animation. I recieved my PhD in CSE from the University of Washington working with Profs. Sham Kakade and Emo Todorov. During this time, I also worked closely with Sergey Levine and Chelsea Finn, and spent time as a student researcher at Google Brain and OpenAI. Before that, I recieved my Bachelors degree along with the best undergraduate thesis award from IIT Madras. | |
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Representative Papers A Game Theoretic Framework for Model Based Reinforcement Learning MOReL : Model-Based Offline Reinforcement Learning Meta Learning with Implicit Gradients Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control | |
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Mentoring I enjoy collaborating with a diverse set of students and researchers. I have had the pleasure of mentoring some highly motivated students at both the undergraduate and PhD levels. | |
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All Publications and Preprints | |
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Teaching
CSE599G: Deep Reinforcement Learning (Instructor)
CSE547: Machine Learning for Big Data (Teaching Assistant)
CSE546: Machine Learning (Teaching Assistant) | |
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