I am a resarcher in Machine Learning. I did a PhD at the Department of Computer Science in the University of Oxford, where I was advised by Shimon Whiteson. My long term research goal is to create theoretically grounded methods for intelligent agents which scale to large, real-life scenarios.

My research at Oxford was supported by J.P. Morgan A.I. Fellowship, Google-DeepMind Scholarship and Draper’s Scholarship. Previously, I have also spent time at DeepMind, J.P. Morgan A.I. and Nvidia. Even before that, I did my undergraduate degree in Computer Science at the Indian Institute of Technology, Delhi after which I worked as a research scientist at Xerox Research. I currently work at Amazon where I lead the efforts at the intersection of Reinforcement Learning and Generative AI for text and image domains. My CV can be found here.


I am interested in understanding the principles of intelligent behaviour and creating algorithms which can help machines learn in practical settings. My current work focuses on themes like Generative AI, large-scale Reinforcement Learning (RL), Natural Language Processing (NLP), Computer Vision, Multi-Agent Systems, Learning Theory, Safety/Alignment in AI with particular emphasis on computational and mathematical foundations. I am also interested in alternate paradigms for learning intelligent behaviour especially towards equipping agents with attributes that help capture aspects like symmetry, compositionality and reasoning under uncertainity in rich multi-modal environments.


  1. Checkout our work on Generalization Across Observation Shifts in Reinforcement Learning, full paper here.
  2. My PhD thesis Reinforcement Learning in Large State Action spaces is now available online here.
  3. Checkout our work on Generalization in Cooperative Multi-Agent Systems, full paper here.
  4. Checkout our work on Open-Ended Learning which leads to Generally Capable Agents, full paper here.
  5. Our work Tesseract using tensor decompositions for factored action spaces accepted for ICML 2021
  6. Our work UneEVen using successor features for exploration in multi agent RL accepted for ICML 2021
  7. I will be starting a research internship at DeepMind in Trinity 2021
  8. Our work RODE using role decomposition for multi agent RL accepted in ICLR 2021
  9. Honoured to be awarded IBM PhD fellowship, 2020
  10. Honoured to be awarded J.P. Morgan A.I. Fellowship, 2020
  11. I will be starting a research internship at J.P. Morgan A.I. in Michaelmas 2020
  12. I will be starting a research internship at Nvidia in Michaelmas 2019
  13. Our work MAVEN using mutual information for efficient exploration in multi agent RL accepted for NeurIPS 2019
  14. Our work VIREL proposing exact equivalence between RL and inference accepted for NeurIPS 2019

Research Opportunities

I am happy to discuss and collaborate on topics related to my research interests. If you are interested, please send me an email. I especially encourage students from under-represented groups and motivated graduate students to reach out.