His research focuses on the development of algorithms for Machine Learning with application to Natural Language Processing and Material Design. He is most well known for his contributions to the development of Reinforcement Learning algorithms. Notable projects that his research team are currently working on include Bayesian federated learning, probabilistic deep learning, data efficient reinforcement learning, conversational agents, automated document editing, sport analytics, adaptive satisfiability and CO2 conversion & capture.

Pascal Poupart received a Canada CIFAR AI Chair at the Vector Institute (2018-present), outstanding performance awards at the University of Waterloo (2017, 2021), a Cheriton Faculty Fellowship (2015-2018), a best student paper honourable mention (SAT-2017), a silver medal at the SAT-2017 competition, a top reviewer award (ICML-2016), a gold medal at the SAT-2016 competition, a best reviewer award (NIPS-2015), an Early Researcher Award from the Ontario Ministry of Research and Innovation (2008), two Google reserch awards (2007-2008), a best paper award runner up (UAI-2008) and the IAPR best paper award (ICVS-2007). He serves as member of the editorial board of the Journal of Machine Learning Research (JMLR) (2009 - present), action editor for Transactohns of Machine Learning Research (TMLR) (2022 - present) and guest editor for the Machine Learning Journal (MLJ) (2012 - present). He routinely serves as area chair or senior program committee member for NeurIPS, ICML, AISTATS, ICLR, IJCAI, AAAI and UAI. His research collaborators include Microsoft, RBC Borealis AI, Google, Manulife, Intel, Ford, ProNavigator, SportLogic, Scribendi, Kik Interactive, In the Chat, Slyce, HockeyTech, the Alzheimer Association, the UW-Schlegel Research Institute for Aging, Sunnybrook Health Science Centre and the Toronto Rehabilitation