About Me

Hello and வணக்கம் 👋! I am Prashant Govindarajan, a second year Computer Engineering PhD student at Mila-Quebec AI Institute and Polytechnique Montréal (engineering school of UdéM), working under Sarath Chandar. I am keenly interested in AI for scientific discovery focusing on drug and material design, and I’ve lately been working on the latter. I am primarily exploring reinforcement learning and geometric deep learning approaches. My current project, which is in collaboration with Intel, is on developing offline reinforcement learning methods for material design using first-principles. I was previously a dual degree student at the Indian Institute of Technology Madras, where I worked under Balaraman Ravindran and Karthik Raman on target-specific drug design.

Besides academics, I like watching and playing football, reading, and cooking (photos coming up soon!). Feel free to reach out to me if you wish to have a chat about research and beyond 😁! Also, I am always looking forward to strengthening my foundations in crystallography, density functional theory, and solid-state physics, and getting domain-related inputs for my research. So if you have a background in these areas or wish to discuss about the RL aspects of my research, I’d love to have a conversation some time!


  • May 2024 Attended Sciencepreneurship Summer School at EPFL, Switzerland, and our team won the first place in the pitch competition!
  • April 2024 Passed my quals! I’m a PhD Candidate now!
  • March 2024 Organizing MoML Conference (summer edition) for the second time (MoML 2024)!
  • January 2024 Learning Conditional Policies for Crystal Design Using Offline Reinforcement Learning accepted for the AI4Mat-2023 Digital Discovery Special Issue!
  • December 2023 Presented poster at AI4Mat Workshop at NeurIPS 2023, New Orleans
  • November 2023 Volunteer for Graduate Application Assistance Program for Underrepresented Students in AI
  • November 2023 Presented poster at MoML 2023, MIT
  • August 2023 Teaching assistant for INF8250AE, Reinforcement Learning by Sarath Chandar
  • August 2023 Attended Conference on Lifelong Learning Agents (CoLLAs) in Montéal
  • March 2023 Behavioral Cloning for Crystal Design accepted as workshop paper at ML4Materials workshop, ICLR 2023
  • February 2023 Organizer of Molecular ML Conference (MoML 2023) happening on May 29, 2023
  • November 2022 Reviewer for Depolyable AI workshop at AAAI 2023
  • August 2022 Started PhD in Computer Engineering at Mila and Polytechnique Montreal, advised by Sarath Chandar
  • July 2022 Graduated from IIT Madras with a dual degree in Biological Sciences and Data Science
  • June 2022 Defended M.Tech thesis titled “Graph generative models for binding site-specific molecule generation”
  • May 2022 “Generating drug-like molecules from gene expression signatures using transformer model” accepted as poster at MLCSB-COSI, ISMB 2022
  • April 2022 Presented poster for thesis work at RBCDSAI Annual Research Showcase
  • April 2022 Selected for international travel bursary to attend Amii’s AI Week 2022
  • January 2022 Teaching assistant for CS6700, Reinforcement Learning by Balaraman Ravindran
  • August 2021 Teaching assistant for BT3051, Data Structures and Algorithms for Biology by Karthik Raman
  • January 2020 Selected for the Khorana Program for Scholars to undertake research internship in the USA