About Me

I am a Ph.D student at the Department of Electrical and Computer Engineering at McGill University. I am working at Systems and Control Group, Center for Intelligent Machines (CIM). I am affiliated with Montreal Institute of Learning Algorithms (MILA). I am supervised by Professor Aditya Mahajan and co-supervised by Professor Jerome Le Ny.

I completed my Master's degree in Electrical and Computer Engineering from McGill University and my undergraduate degree in Electrical and Electronic Engineering from Islamic University of Technology. I was a former Research Scientist intern at Aerial Technologies, Montreal Canada where my research focussed on learning algorithms for real-time indoor localization using wireless signals. After completing my undergraduate studies, I worked as a Research Engineer at the Department of Biomedical Physics and Technology University of Dhaka, Bangladesh under the supervision of Professor Siddique-e-Rabbani.

Research Interest

I am primarily interested in using Machine Learning algorithms for achieving optimal control for multi-agent systems. My research is therefore at the intersection of Reinforcement Learning and Control Systems for intelligent control applications. I work on control sharing in human automation team problems.


Doctor of Philosophy

McGill University 2019-Present
Research Area: Multi-agent Reinforcement Learning, Game Theory, Machine learning. Supervisor(s): Aditya Mahajan and Jerome Le Ny

Awards and Honors

  • McGill Engineering Doctoral Award(MEDA) (2019-2022).
  • GERAD co-supervised student award (2019).
  • Mitacs Accelerate Fellowship (2018).
  • Recepient of Graduate Excellence Fellowship at McGill (2017,2018,2021).
  • Member of the winning team of Brac Manthan Award for e health catagory (2016).
  • OIC scholarship (for academic excellence in university entrance examination) (2011).
  • Recipient of the Daily Star Award for academic excellence in O and A levels (2011).


  • Raihan Seraj, Jivitesh Sharma and Ole-Christoffer Granmo "Tsetlin Machine for Solving Contextual Bandit Problems". In 36th Conference on Neural Information Processing Systems (NeurIPS). [pdf]

  • Raihan Seraj, Jerome Le Ny and Aditya Mahajan "Mean-field approximation for large-population beauty-contest games". In 2021 IEEE 60th Conference on Decision and Control (CDC).[pdf]

  • Jayakumar Subramanian, Amit Sinha, Raihan Seraj and Aditya Mahajan. "Approximate information state for approximate planning and reinforcement learning in partially observed systems." Journal of Machine Learning Research (JMLR).[pdf]

  • Jayakumar Subramanian, Raihan Seraj and Aditya Mahajan ”Reinforcement learning for mean-field teams” AAMAS Workshop on Adaptive and Learning Agents, Montreal, Canada, 13-17 May, 2019. [pdf]

  • Riashat Islam, Raihan Seraj, Pierre-Luc Bacon, Doina Precup. “Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods”, NeurIPS 2019 workshop on Optimization Foundations for Reinforcement Learning. [pdf]

  • Riashat Islam, Raihan Seraj, Samin Yeasar Arnob, Doina Precup. “Doubly Robust Off-Policy Actor Critic Algorithms for Reinforcement Learning”, NeurIPS 2019 workshop on Safety and Robustness in Decision Making. [pdf]

  • Raihan Seraj, Mohiuddin Ahmed ”Concept drifts for big data”, Combating Security Challenges in the Age of Big Data - Powered by State-of-theArt Artificial Intelligence Techniques, Springer.[pdf]

  • Ahmed, Mohiuddin, Raihan Seraj, and Syed Mohammed Shamsul Islam. "The k-means algorithm: A comprehensive survey and performance evaluation." Electronics 9.8 (2020): 1295.[pdf]


  • 14-Sep-2022 Paper titled "Tsetlin Machine for Solving Contextual Bandit Problems" got accepted at Neural Information Processing Systems (NeurIPS) 2022.
  • 9-Sept-2021 Successfully completed my PhD thesis proposal examination.
  • 1-Jul-2021 Joined Valence Drug Discovery for Scientist in Residence Program.
  • 27-Jul-2021 Paper titled "Mean-field approximation for large-population beauty-contest games" got accepted at IEEE Conference on Decision and Control (CDC) 2021.
  • 1-Aug-2021 Paper titled "Approximate information state for approximate planning and reinforcement learning" got accepted at Journal of Machine Learning Research (JMLR).
  • 24-Feb-2020 Successfully completed my PhD comprehensive examination.
  • 1-Jan-2019 Started my PhD at the department of Electrical and Computer Engineering.
  • 31-Dec-2018 Successfully completed my Masters degree from the department of Electrical and Computer Engineering.
  • 1-Mar-2018 Joined Aerial Technologies as a Research Scientist Intern.
  • 1-Jan-2017 Started graduate school at the department of Electrical and Computer Engineering, McGill Univeristy.
  • 31-Dec-2015 Started a job as a Research Engineer at the Department of Biomedical Physics and Technology, University of Dhaka.
  • 25-Dec-2015 Graduated with first class honors from the department of Electrical and Electronic Engineering, Islamic University of Technology.

Curriculum Vitae