Sriram is an Assistant Professor at the School of Computer Science in Carleton University. He is also a Faculty Affiliate at the Vector Institute, Toronto, and the Schwartz Reisman Institute for Technology and Society, Toronto. His primary research interest is in the area of multi-agent reinforcement learning. Particularly, he is interested in the problems of scale, non-stationarity, effective communication, and sample inefficiency in multi-agent learning systems. His long-term research vision is to make multi-agent learning algorithms applicable to a variety of large-scale real-world problems and to bridge the widening gap between the theoretical understanding and empirical advances of multi-agent reinforcement learning. As a consequence of his research interests, he frequently works on the broad areas (and the intersections) of Reinforcement Learning, Machine Learning, and Game Theory. Previously, Sriram was a Distinguished Postdoctoral Fellow at the Vector Institute. He obtained his PhD in Electrical and Computer Engineering from the University of Waterloo. His doctoral dissertation won the Best Doctoral Dissertation Award from the Canadian AI Association.  Sriram’s research has been published in several top-tier multi-agent and AI venues such as AAAI, AAMAS, ICML, AISTATS, IJCAI, and JAIR. During his research journey, Sriram has collaborated closely with multiple companies, including Microsoft, Royal Bank of Canada, Denso International America, Environmental Systems Research Institute (ESRI), and the Bank of Montreal. 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.