I am a researcher in the Reinforcement Learning group at Microsoft Research AI, Redmond, USA. I also work closely with the Reinforcement Learning groups at MSR NYC and the research team of Chief Science Officer (Eric Horvitz).
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.
As of January 2019 I am also serving as Affiliate Assistant Professor at The School of Computer Science and Engineering, University of Washington, Seattle, USA.
I regularly review for NeurIPS, ICLR, ICML. On occasion for ICRA, IROS, IJRR, JFR, CVPR, ECCV, ICCV.
Work email: dedey microsoft com
Personal email: dey at debadeepta com
03/2020: Area chair for Neurips 2020.
02/2020: MSR podcast on my research philosophy!
11/2019: Area chair for ICML 2020.
11/2019: Using RL to optimize software pipelines accepted at AAAI 2020.
10/2019: Invited to NSF Panel on Robotics and Speech at UMD.
09/2019: Efficient Forward Architecture Search accepted to NeurIPS 2019.
09/2019: Top 50% reviewer at NeurIPS 2019.
06/2019: MSR blog post on visual navigation via language assistance.
04/2019: Metareasoning in Modular Software Systems using RL is public, Real-World RL ICML workshop.
03/2019: Paper on visual navigation via language assistance accepted to CVPR 2019.
02/2019: Outstanding reviewer award ICLR 2019.
01/2019: Invited to CCC-NSF Robotics and Learning Workshop in San Francisco.
10/2018: Invited talk on Interactive Machine Learning at UMD.
10/2018: Two papers accepted at AAAI 2019. Anytime Neural Networks selected for oral presentation.
10/2018: Top reviewer award NeurIPS 2018.
09/2018: Invited talk on Robotics and Imitation Learning at New York University.
09/2018: Invited talk on Imitation Learning at Reinforcement Learning Day at MSR New York.
08/2018: Organizer of session on 'AI for AI Systems' at MSR Faculty Summit 2018.
07/2018: Invited talk at UW-MSR Summer Retreat on Social Robotics.
06/2018: Paper on Learning 3D View Utilities accepted at ECCV 2018.
06/2018: Invited talk at RSS Workshop on Resilient Robotics.
02/2018: Paper on Blind Spots in RL accepted to AAMAS 2018.
02/2018: Journal version of Learning to Gather Information accepted at IJRR.
01/2018: Invited talk at The Robotics Institute, Carnegie Mellon University.
12/2017: Visiting MSR Bangalore.
10/2017: Upcoming invited talk at ICCV 2017 Workshop on Role of Simulation in Computer Vision.
08/2017: Paper on efficient 3D scanning accepted at ICCV 2017.
07/2017: Paper describing AirSim accepted at FSR 2017.
06/2017: Invited talk at International Symposium on Aerial Vehicles at University of Pennsylvania.
05/2017: Paper on efficient route planning leveraging multi-armed bandits accepted at ICML 2017.
04/2017: Paper on adaptive information gathering accepted at RSS 2017.
03/2017: Paper on UAV tracking using flight dynamics accepted for oral presentation at CVPR 2017.
02/2017: We released open-source photo-realistic robotics simulator AirSim.
01/2017: Two papers accepted at ICRA 2017.
12/2016: Sponsorship and Publicity Chair of Conference on Robot Learning.
10/2016: Invited talk at workshop on "Vision-based High Speed Autonomous Navigation of UAVs", IROS 2017.
08/2016: Invited to NSF-UAS Advisory Board meeting at Dayton, OH.
07/2016: Co-organized workshop on "Safe-Cyber Physical Systems" at Faculty Summit, Microsoft Research.
06/2016: Presented at RSS Workshop on Task and Motion Planning at University of Michigan, Ann Arbor.
10/2015: Trajectory optimization for Team Chambliss at Red Bull Air Race at Dallas, TX.
08/2015: Joined Microsoft Research.
07/2015: Defended PhD thesis at Carnegie Mellon University.
Microsoft Research AI, Redmond
Microsoft Research AI, Redmond
The Robotics Institute, Carnegie Mellon University
Field Robotics Center, Carnegie Mellon University
Research Technology Associate
Dilip Arumugam, Stanford (Summer 2019)
Roshan Rao, UC Berkeley (Summer 2019)
Angela Lin, UT Austin (Summer 2019)
Prasoon Goyal, UT Austin (Summer 2019)
Khanh Nguyen, UMD (Summer 2018)
Aditya Modi, Univ. of Michigan (Summer 2018)
Hanzhang Hu, CMU (Summer 2018)
Elizabeth Bondi, USC (Fall 2017)
Ramya Ramakrishnan, MIT (Summer 2017, Summer 2018)
Simon Ramstedt, TU Darmstadt (Summer 2017)
Benjamin Hepp, ETH Zurich (Summer 2017)
Felix Berkenkamp, ETH Zurich (Summer 2017)
Sanjiban Choudhury, CMU (Summer 2016)
Brian Axelrod, MIT (Summer 2016)
Wen Sun, CMU (Summer 2016)
Artem Rozantsov, EPFL (Summer 2016)
Mike Roberts, Stanford (Summer 2016, 2017)
Francisco Garcia, University of Massachusetts, Amherst, (Fall 2016)