Nitin Kamra Research Scientist
Reality Labs Research, Meta

About me


I am a Research Scientist at Reality Labs Research, Meta. I work on developing efficient planning and reinforcement learning algorithms to enable household assistive agents in AR/VR to provide guidance to users for day-to-day tasks.

Earlier, I graduated with an MS in Intelligent Robotics and a Ph.D. in Computer Science from the University of Southern California (USC) in May 2021. I was advised by Yan Liu in the Melady Lab. My research was primarily focused on prediction and control in multi-agent settings with dense interactions amongst the various agents. I also worked on several projects involving reinforcement learning, continual learning, game theory, robotics, natural language understanding and graph-based relational learning.

Before this, I attended Indian Institute of Technology, Delhi (2010-2014) for my undergraduate degree in Electrical Engineering, with focus on Control Theory and Signal Processing. I was advised by Shouribrata Chatterjee. I was also the Technical Secretary of the Electrical Engineering Society and served as the General Secretary of the Electronics Club during my final year at IIT Delhi.

My broad research interest lies in understanding "understanding" itself. As an ambitious goal, I want to figure out how the human mind works and potentially develop architectures and algorithms for artificial agents to achieve at least the same level of understanding as humans one day. Consequently, I work on reinforcement learning and deep learning to design agents capable of autonomous planning and learning in multi-agent settings. My research interests broadly span deep reinforcement learning, continual learning, planning, multi-agent learning, natural language understanding and robotics.

Research & Publications


Learning and Planning for Embodied AI Agents

  1. Task Optimization in an Extended Reality Environment
    Ruta Parimal Desai and Nitin Kamra
    US Patent Application 20230342677 -- Filed 21 Apr, 2023
    Meta Reality Labs Research
  2. Human-Centered Planning
    Yuliang Li, Nitin Kamra, Ruta Desai and Alon Halevy
    ArXiv, Nov 2023
  3. Pretrained Language Models as Visual Planners for Human Assistance
    Dhruvesh Patel, Hamid Eghbalzadeh, Nitin Kamra, Michael Louis Iuzzolino, Unnat Jain and Ruta Desai
    International Conference on Computer Vision (ICCV), Oct 2023
    A shorter version also in ICCV Workshop on Assistive Computer Vision and Robotics (ACVR), Oct 2023
  4. EgoTV: Egocentric Task Verification from Natural Language Task Descriptions
    Rishi Hazra, Brian Chen, Akshara Rai, Nitin Kamra and Ruta Desai
    International Conference on Computer Vision (ICCV), Oct 2023
  5. Action Dynamics Task Graphs for Learning Plannable Representations of Procedural Tasks
    Weichao Mao, Ruta Desai, Michael Louis Iuzzolino and Nitin Kamra
    AAAI Workshop on User-Centric Artificial Intelligence for Assistance in At-Home Tasks, Feb 2023
  6. Effective Baselines for Multiple Object Rearrangement Planning in Partially Observable Mapped Environments
    Engin Tekin, Elaheh Barati, Nitin Kamra and Ruta Desai
    AAAI Workshop on User-Centric Artificial Intelligence for Assistance in At-Home Tasks, Feb 2023

Learning in Multi-agent Systems

  1. Machine Learning in Interacting Multi-agent Systems
    Nitin Kamra
    PhD Thesis (University of Southern California), July 2021
  2. Gradient-based Optimization for Multi-resource Spatial Coverage Problems
    Nitin Kamra and Yan Liu
    Conference on Uncertainty in Artificial Intelligence (UAI), July 2021
  3. Gradient-based Optimization for Multi-resource Spatial Coverage
    Nitin Kamra and Yan Liu
    NeurIPS workshop on Interpretable Inductive Biases and Physically Structured Learning, 2020
  4. Multi-agent Trajectory Prediction with Fuzzy Query Attention
    Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang and Yan Liu
    Advances in Neural Information Processing Systems (NeurIPS), 2020
  5. Where is the World Headed? Trajectory Prediction for Interacting Agents
    Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang and Yan Liu
    Southern California Machine Learning Symposium (SCMLS), 2020
  6. DeepFP for Finding Nash Equilibrium in Continuous Action Spaces
    Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu and Milind Tambe
    Conference on Decision and Game Theory for Security (GameSec), 2019
  7. Deep Fictitious Play for Games with Continuous Action Spaces
    Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu and Milind Tambe
    International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2019
  8. Policy Learning for Continuous Space Security Games using Neural Networks
    Nitin Kamra, Umang Gupta, Fei Fang, Yan Liu and Milind Tambe
    AAAI Conference on Artificial Intelligence (AAAI), February 2018
  9. Handling Continuous Space Security Games with Neural Networks
    Nitin Kamra, Fei Fang, Debarun Kar, Yan Liu and Milind Tambe
    IJCAI International Workshop on A.I. in Security (IWAISe), August 2017

Machine Learning for Healthcare

  1. Treatment Recommendation with Preference-based Reinforcement Learning
    Nan Xu, Nitin Kamra and Yan Liu
    IEEE International Conference on Big Knowledge (ICBK), 2021
  2. PolSIRD: Modeling Epidemic Spread under Intervention Policies
    Nitin Kamra, Yizhou Zhang, Sirisha Rambhatla, Chuizheng Meng and Yan Liu
    Journal of Healthcare Informatics Research (J-HIR), Jun 2021
  3. An Examination of Preference-based Reinforcement Learning for Treatment Recommendation
    Nan Xu, Nitin Kamra and Yan Liu
    NeurIPS workshop on Deep Reinforcement Learning, 2020

Multi-robot Systems

  1. Combinatorial Problems in Multi-Robot Battery Exchange Systems
    Nitin Kamra, T. K. Satish Kumar and Nora Ayanian
    IEEE Transactions on Automation Science and Engineering (T-ASE), 2018
  2. A mixed integer programming model for timed deliveries in multirobot systems
    Nitin Kamra and Nora Ayanian
    IEEE International Conference on Automation Science and Engineering (CASE), August 2015
  3. RF-Based Relative Localization for Robot Swarms
    Wolfgang Hoenig and Nitin Kamra
    Project, Spring 2015

Natural Language Understanding

  1. Towards Zero-shot Dialog Act Classification
    Nitin Kamra, Daniel Elkind and Angeliki Metallinou
    Alexa Natural Understanding, Amazon. Summer 2020
  2. Correction of Speech Recognition on Repetitive Queries
    Pinar Donmez Ediz, Ranjitha Kulkarni, Shawn Chang and Nitin Kamra
    US patent 10,650,811 -- Issued May 12, 2020
    Microsoft AI and Research, Sunnyvale CA, Summer 2017

Miscellaneous

  1. Deep Generative Dual Memory Network for Continual Learning
    Nitin Kamra, Umang Gupta and Yan Liu
    ArXiv, May 2018
  2. DynGEM: Deep Embedding Method for Dynamic Graphs
    Nitin Kamra*, Palash Goyal*, Xinran He and Yan Liu
    IJCAI International Workshop on Representation Learning for Graphs (ReLiG), August 2017
  3. Parallel Gradient Descent for Multilayer Feedforward Neural Networks
    Nitin Kamra, Palash Goyal, Sungyong Seo and Vasilis Zois
    Project, Spring 2016
  4. Predicting Rainfall with Polarimetric Radar Data
    Nitin Kamra and James Preiss
    Kaggle Competition, Fall 2015
  5. Output Power Maximization in Energy Harvesting Applications
    Nitin Kamra and Shouribrata Chatterjee
    Undergraduate Thesis (IIT Delhi), 2014
  6. ROSHNI: Indoor Navigation System for Visually Impaired
    Nitin Kamra, Devesh Singh, Dhruv Jain and M. Balakrishnan
    Project, Spring 2012
  7. Elementary Iterative Methods and the Conjugate Gradient Algorithm
    Nitin Kamra
    High Performance Computing, Indo-German Winter Academy, December 2012

Teaching


  • Teaching Assistant for CS-567: Machine Learning, USC (Spring 2020, Fall 2016)

  • Tutorial for Reinforcement Learning, CS-699: Advanced topics in Deep Learning, USC (Spring 2019)

  • Hosting the Artificial General Intelligence Reading Group at USC (Fall 2018)

  • Teaching Assistant for EEL301: Control Engg - I, IIT Delhi (Spring 2014)

  • Teaching Assistant for EEL201: Digital Electronics, IIT Delhi (Fall 2013)

Awards


  • Deep Learning Best Theory Project Award, CS-599: Deep Learning, University of Southern California (2017)

  • Viterbi Graduate Ph.D. Fellowship, University of Southern California (2014-18)

  • Best Mentor Award, Awarded by Mentorship Review Committee, Indian Institute of Technology, Delhi (2013)

  • SOF 3rd International Mathematics Olympiad, International Rank 16, School Topper and Gold Medalist (2010)

  • SOF 12th National Science Olympiad, National Rank 45, School Topper and Gold Medalist (2010)

  • FIITJEE Talent Reward Exam, Zonal Topper and Gold Medalist (2009)