Irina Rish is a Full Professor in the Department of Computer Science and Operations Research at the Faculty of Arts and Sciences of the Université de Montréal (UdeM). She holds the CIFAR-Canada AI Chair and the Canada Excellence Research Chair in Autonomous AI.

Her research focuses on machine learning, neural data analysis, and neuroscience-inspired AI.

Her current research interests include continual learning, optimization algorithms for deep neural networks, sparse modeling and probabilistic inference, dialogue generation, biologically plausible reinforcement learning, and dynamic systems approaches to brain imaging analysis. Before joining UdeM and Mila in 2019, she was a researcher at IBM's T. J. Watson Research Center, where she worked on various projects at the intersection of neuroscience and AI and led the Neuro-AI challenge. Irina Rish holds 64 patents, has published over 80 research papers, several book chapters, three edited volumes, and a monograph on sparse modeling.