Address: Microsoft Research,
641 6th Ave, New York,
New York, 10011

Dipendra Misra

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).

Research Interests: My main interest is in developing provable and practically efficient algorithms with application to real-life problems. My main emphasis is on problems in natural language understanding and allied fields. I am currently active in the following research areas: reinforcement learning theory, interactive learning, language and vision problems.


Quick Links:   A Bandit Game,   CIFF Code Base,   My Blog,   RL Formulas

Research and Publication

I am interested in developing models and learning methods with emphasis on applications in natural language understanding such as robots that can follow instruction, answer questions or hold a conversation. I am currently active in three research areas:

  • Robot Instruction Following: Robots that can follow instructions can be of great assistance. I am interested in developing models that can train with minimal effort and generalize to new environments and instructions. See Misra et al. EMNLP 2018b, EMNLP 2017, ACL 2015a, IJRR 2015b, RSS 2014.

  • Semantic parsing: I am interested in developing semantic parsers using weak supervision with application to tasks like question answering. See Misra et al. EMNLP 2018a and Misra and Artzi EMNLP 2016.

  • Reinforcement Learning: Problems described above are often best described using a reinforcement learning framework. I am interested in developing reinforcement learning algorithms that simultaneously achieve good exploration, sample efficiency and generalization with theoretical guarantees. See Misra et al. EMNLP 2017 and Asadi, Misra, Littman ICML 2018.

I have served or serving as program committee member for natural language processing (EMNLP, ACL, EACL, NAACL), machine learning (ICML, NIPS, AISTATS) and robotics conferences and journals (JAIR, ICRA, HRI, ISRR, RSS).


Preprint

Combating the Compounding-Error Problem with a Multi-step Model
Kavosh Asadi, Dipendra Misra, Seungchan Kim, Michel L Littman
arXiv report, 2018.
[Paper]



Conference

Early Fusion for Goal Directed Robotic Vision
Aaron Walsman, Yonatan Bisk, Saadia Gabriel, Dipendra Misra, Yoav Artzi, Yejin Choi, Dieter Fox
In International Conference on Intelligent Robots and Systems (IROS), 2019.
[Paper]    [Best paper nomination]

Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments
Howard Chen, Alane Suhr, Dipendra Misra, Noah Snavely, Yoav Artzi
In Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[Paper] [Dataset and SDR Code] [Navigation Code]

Mapping Navigation Instructions to Continuous Control Actions with Position Visitation Prediction
Valts Blukis, Dipendra Misra, Ross A. Knepper, and Yoav Artzi
In Proceedings of the Conference on Robot Learning (CoRL), 2018.
[Paper] [Code] [Demo Video]

Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations
Dipendra Misra, Ming-Wei Chang, Xiaodong He and Wen-tau Yih
In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
[Paper] [Code]

Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction
Dipendra Misra, Andrew Bennett, Valts Blukis, Eyvind Niklasson, Max Shatkhin, and Yoav Artzi
In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
[Paper] [Code, Data and Simulators]

Lipschitz Continuity in Model-based Reinforcement Learning
Kavosh Asadi*, Dipendra Misra*, Michael L. Littman (* equal contribution)
In Proceedings of the 35th International Conference on Machine Learning (ICML), 2018.
[Paper] [Code]

Mapping Instructions and Visual Observations to Actions with Reinforcement Learning
Dipendra Misra, John Langford and Yoav Artzi
In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
[Paper] [Code] [Arxiv Preprint]

Neural Shift-Reduce CCG Semantic Parsing
Dipendra Misra and Yoav Artzi
In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016.
[Paper] [Supplementary] [Code]

Environment-driven lexicon induction for high-level instructions
Dipendra K. Misra, Kejia Tao, Percy Liang, Ashutosh Saxena
In Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2015.
[Paper] [Supplementary] [Code] [Data] [Simulator] [Bibtex]

Robo Brain: Large-Scale Knowledge Engine for Robots
Ashutosh Saxena, Ashesh Jain, Ozan Sener, Aditya Jami, Dipendra K. Misra, Hema S Koppula
In Proceedings of the International Symposium of Robotics Research (ISRR), 2015.
[Paper] [Website]

Tell Me Dave: Context-Sensitive Grounding of Natural Language to Manipulation Instructions
Dipendra K. Misra, Jaeyong Sung, Kevin K. Lee, Ashutosh Saxena
In Proceedings of the Robotics: Science and systems (RSS), 2015.
[Paper] [Website] [Simulator] [Bibtex]


Journal:

Tell Me Dave: Context-Sensitive Grounding of Natural Language to Manipulation Instructions
Dipendra K. Misra, Jaeyong Sung, Kevin K. Lee, Ashutosh Saxena
In The International Journal of Robotics Research (IJRR), 2015.
[Paper] [Website] [Bibtex]




Workshop

Towards a Simple Approach to Multi-step Model-based Reinforcement Learning
Kavosh Asadi, Evan Carter, Dipendra Misra, Michael Littman
Deep Reinforcement Learning Workshop at the Conference on Neural Information Processing Systems (NeurIPS), 2018.
[Paper]

The Third Workshop on Representation Learning for NLP (Rep4NLP)
Isabelle Augenstein, Kris Cao, He He, Felix Hill, Spandana Gella, Jamie Kiros, Hongyuan Mei and Dipendra Misra
Workshop at the Annual Meeting of the Association for Computational Linguistics (ACL), 2018.
[Workshop Proceedings]

Equivalence Between Wasserstein and Value-Aware Model-based Reinforcement Learning
Kavosh Asadi, Evan Carter, Dipendra Misra and Michael L. Littman
Workshop on Prediction and Generative Modeling in Reinforcement Learning (PGMRL) at the International Conference on Machine Learning (ICML), 2018.
[ArXiv Preprint]

CHALET: Cornell House Agent Learning Environment
Claudia Yan, Dipendra Misra, Andrew Bennett, Aaron Walsman, Yonatan Bisk and Yoav Artzi
arXiv report, 2018.
[Paper] [Website] [Bibtex]

Reinforcement Learning for Mapping Instructions to Actions with Reward Learning
Dipendra Misra and Yoav Artzi
Symposium on Natural Communication for Human-Robot Collaboration at AAAI Fall Symposium Series, 2017.
[Paper] [Code]

Posts

  • PAC with Hoeffding-Bernstein    [Post]

  • Growing Bifurcation of AI Scholarship     [Post]

  • Dynkin’s π-λ Theorem and CDF     [Part 1]     [Part 2]

  • Are Synthetic Datasets in AI Useful?     [Post]

  • Are we doing NLP the right way?     [Post]

  • Writing and Proof Reading Research Code     [Post]

  • Getting into Top CS PhD Programs in the US     [Post]

  • Mathematical Analysis of Policy Gradient Methods     [Post]

  • Tutorial on Markov Decision Process Theory and Reinforcement Learning.     [Slides Part 1]     [Slides Part 2]     [Post]

Misc

I received my bachelors degree in computer science from the Indian Institute of Technology, Kanpur where my undergrad thesis on learning to solve IQ questions was advised by Amitabha Mukerjee and Sumit Gulwani. My studies at time have been supported by OPJEMS Merit scholarship (2011-12 and 2012-13), Cornell University Fellowship (2013) and amazon AWS Research grant (2016). I try to spend some time playing piano, writing compositions and reading news.