I am a Principal Researcher in the Reinforcement Learning group at Microsoft Research AI, Redmond, USA.
I finished my PhD at the Robotics Institute, Carnegie Mellon University, USA, where I was advised by Prof. J. Andrew (Drew) Bagnell. I do fundamental as well as applied research in machine learning, control and computer vision with applications to autonomous agents in general and robotics in particular.
My interests include decison-making under uncertainty, reinforcement learning, artificial intelligence and machine learning. I regularly area-chair/review for NeurIPS, ICLR, ICML. On occasion for ICRA, IROS, IJRR, JFR, CVPR, ECCV, ICCV.
For latest news and updated publication list see my personal page.
Microsoft Research Podcast
Episode 108 | February 26, 2020 - Dr. Debadeepta Dey is a Principal Researcher in the Adaptive Systems and Interaction group at MSR and he’s currently exploring several lines of research that may help bridge the gap between perception and planning for autonomous agents, teaching them to make decisions under uncertainty and even to stop and ask for directions when they get lost! On the podcast, Dr. Dey talks about how his latest work in meta-reasoning helps improve modular system pipelines and how imitation learning hits the ML sweet spot between supervised and reinforcement learning. He also explains how neural architecture search helps enlighten the “dark arts” of neural network training and reveals how boredom, an old robot and several “book runs” between India and the US led to a rewarding career in research.