ஜனார்த்தனன் ராஜேந்திரன்
Janarthanan Rajendran (he/him)
வணக்கம் (~ Greetings in Tamil) :)
I am an IVADO Postdoctoral Research Fellow at Mila - Quebec Artificial Intelligence Institute and the University of Montréal, working with Prof. Sarath Chandar and Prof. Doina Precup.
My research interests lie in building systems that through interaction can learn to be competent in complex, dynamic, and uncertain environments. I am interested in the computational methods to build such systems as well as their practical applications and societal implications. To this end, my current research focuses on deep reinforcement learning and natural language processing.
I completed my Ph.D. in Computer Science and Engineering (stream: Artificial Intelligence) at the University of Michigan, Ann Arbor, working with Prof. Satinder Singh, and completed my M.Tech. and B.Tech. in Electrical Engineering (major stream: Communication Engineering, minor stream: Physics) at the Indian Institute of Technology Madras, working with Prof. Balaraman Ravindran and Prof. Kaushik Mitra.
I am always up for a chat :) Send me an email if you would like to discuss anything!
E-Mail (rjana@umich.edu) | LinkedIn | Google Scholar | arXiv
I am currently looking for a tenure-track faculty position :) Please reach out to me if you think there is a good fit.
News (~ past year)
May 2023: Our work Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning, Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran, has been accepted at the Conference on Uncertainty in Artificial Intelligence (UAI) 2023.
May 2023: Our work Replay Buffer with Local Forgetting for Adaptive Deep Model-Based Reinforcement Learning, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar, has been accepted at the Conference on Lifelong Learning Agents (CoLLAs) 2023.
May 2023: Our work Towards Few-shot Coordination: Revisiting Ad-Hoc Teamplay Challenge in the Game of Hanabi, Hadi Nekoei, Xutong Zhao, Janarthanan Rajendran, Miao Liu, Sarath Chandar, has been accepted at the Conference on Lifelong Learning Agents (CoLLAs) 2023.
March 2023: Our work Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning, Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran, is now up on arXiv.
Feb 2023: Our work Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning, Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, Sarath Chandar, is now up on arXiv.
Nov 2022: Our work Replay Buffer with Local Forgetting for Adaptive Deep Model-Based Reinforcement Learning, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar, has been accepted at the Workshop on Deep Reinforcement Learning at NeurIPS 2022.
Oct 2022: Our work PatchBlender: A Motion Prior for Video Transformers, Gabriele Prato, Yale Song, Janarthanan Rajendran, Devon Hjelm, Neel Joshi, Sarath Chandar, has been accepted at Workshop on Vision Transformers: Theory and Applications at NeurIPS 2022.
Aug 2022: Conference on Lifelong Learning Agents (CoLLAs) 2022!
July 2022: Our work An Introduction to Lifelong Supervised Learning, Shagun Sodhani, Mojtaba Faramarzi, Sanket Vaibhav Mehta, Pranshu Malviya, Mohamed Abdelsalam, Janarthanan Janarthanan, Sarath Chandar, is now up on arXiv.
May 2022: Our work Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods, Yi Wan*, Ali Rahimi-Kalahroudi*, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, Harm van Seijen, has been accepted at the International Conference on Machine Learning (ICML) 2022.
Mar 2022: Our work Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods, Yi Wan*, Ali Rahimi-Kalahroudi*, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, Harm van Seijen, has been accepted at the Workshop on Agent Learning in Open-Endedness (ALOE) at ICRL 2022.
Mar 2022: Our work Staged independent learning: Towards decentralized cooperative multi-agent Reinforcement Learning, Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, Sarath Chandar, has been accepted at the Workshop on Gamification and Multi-Agent Solutions at ICLR 2022.