Sriram Subramanian
Assistant Professor & Canada Research Chair
| Degrees: | Ph.D. University of Waterloo (2022), MASc University of Waterloo (2018), BE Anna University (2016). |
| Phone: | 613-520-2600 x 4333 |
| Email: | SriramSubramanian@cunet.carleton.ca |
| Office: | HP5360 |
| Website: | Browse |
Research Interests
Multi-agent Systems, Reinforcement Learning, Game Theory, Deep Learning, Machine Learning, AI Safety, Generative AI
Specific Research Interests
My primary research interest is in the area of multi-agent systems. My research work aims to find effective solutions to the problems of scale, non-stationarity, effective communication, safety, and sample inefficiency in multi-agent learning systems. As a consequence, my area of work is at the intersection of Reinforcement Learning and Game Theory. I am particularly interested in the theoretical aspects of Reinforcement Learning. I have two important and related long-term research goals. The first is to bridge the widening gap between the theoretical understanding and empirical advances of multi-agent reinforcement learning. The second is to make multi-agent learning algorithms applicable to a variety of large-scale real-world problems.
I am particularly interested in research applications of reinforcement learning and multi-agent reinforcement learning in large language models (generative AI), robotics, finance, recommender systems, and autonomous driving.
Biography
Sriram Subramanian is an Assistant Professor at the School of Computer Science in Carleton University, where he holds a Canada Research Chair (Tier II) in Artificial Intelligence. Additionally, he is a Faculty Affiliate at the Vector Institute for Artificial Intelligence, Toronto, and the Schwartz Reisman Institute for Technology and Society, Toronto. He serves as a mentor at the Indigenous Black Engineering and Technology (IBET) PhD Project. During his research journey, Sriram has collaborated with several companies, including Microsoft, Royal Bank of Canada, Denso International America, Environmental Systems Research Institute (ESRI), and the Bank of Montreal. He received his Bachelor’s degree in Engineering from Anna University, Chennai (India) in 2016, a Master’s degree in Electrical and Computer Engineering from the University of Waterloo (Canada) in 2018, and a Ph.D. in Electrical and Computer Engineering from the University of Waterloo (Canada) in 2022. His doctoral dissertation won the Best Doctoral Dissertation Award from the Canadian AI Association in 2023. From September 2022 to June 2025, he was a Distinguished Postdoctoral Fellow at the Vector Institute for Artificial Intelligence, Toronto. His research primarily focuses on the development of novel algorithms and data structures for the fields of Multi-agent Systems, Reinforcement Learning, Game Theory, and Deep Learning. Additionally, his research investigates existing algorithms in these fields either theoretically or empirically, establishing new insights and properties. His work has been published in top-tier journals and conferences in the fields of Multi-agent Systems and Machine Learning, such as ICML, AAMAS, AISTATS, AAAI, IJCAI, JAIR, etc. He also regularly serves as a reviewer and program committee member for top-tier publication venues in the fields of AI, Machine Learning, and Multi-agent Systems.