I am a Senior Researcher at Microsoft Research, New York.
I received my PhD in computer science from Cornell University (2019) and my
bachelors in computer science from Indian Institute of Technology Kanpur (2013).
My main interest is in developing efficient machine learning algorithms with
applications to real-world problems. The word efficient here includes provable,
sample and computationally efficient, interpretable, scalable, and ethical.
My empirical focus is on problems in natural language understanding and allied fields. I am
currently active in reinforcement learning theory, interactive learning,
representation learning, and language and vision problems. One key research agenda is to
develop provably-efficient reinforcement learning algorithms that can be applied to
real-world problems. Another agenda is to develop the theory and practice of
self-supervised representation learning methods. I also have interest
in computational social science, and data and society.
News: We have a new reinforcement learning algorithm HOMER, with theoretical guarantees on
problems with high-dimensional observations that do not depend on the size of observation space. See the current
arXiv. ICML 2020 version and code to be released soon.
We are hiring!
- For post-doc and full-time positions in reinforcement learning
Opinion: ICLR 2020 is going virtual and that is a good thing. Virtual conferences can be better! My post.