Irina Rish is a Full Professor in the Computer Science and Operations Research Department at the Université de Montréal (UdeM). She holds a Canada Excellence Research Chair (CERC) in Autonomous AI. Dr Rish received her MSc and PhD in AI from University of California, Irvine and MSc in Applied Mathematics from Moscow Gubkin Institute. 

Over the past decades,  her research has spanned multiple areas of AI, from automated reasoning, constraint networks and  probabilistic inference in graphical models  to more recent focus on machine learning, sparse modeling,  neural data analysis and neuroscience-inspired AI,  which included neuroscience-inspired learning algorithms  (beyond backpropagation), biologically plausible reinforcement learning,  as well as dynamical systems approaches to brain imaging analysis  dialog generation for (semi)automated therapy.

Irina's current research interests include continual learning, out-of-distribution generalization and robustness of deep neural networks, large-scale models and scaling laws of deep network properties with increasing amounts of data, parameters and compute.  She considers these research areas essential for achieving the holy grail of AI field, Artificial General Intelligence (AGI).

Before joining UdeM in 2019, Irina was a research scientist at the IBM T.J. Watson Research Center, where she worked on various projects at the intersection of neuroscience and AI, and led the Neuro-AI challenge. She received multiple IBM awards, including IBM Eminence & Excellence Award and IBM  Outstanding Innovation Award in 2018, IBM Outstanding Technical Achievement Award in 2017, and IBM Research Accomplishment Award in 2009.  

Dr. Rish holds 64 patents,  has published over 70 peer-reviewed research papers, several book chapters, three edited books, and a monograph on Sparse Modeling. She is IEEE TPAMI Associate Editor (since 2019), a member of the AI Journal (AIJ) editorial board (since 2016), served as a Senior Area Chair for NIPS-2017, NIPS-2018, ICML-2018, an Area Chair for ICLR-2019, ICLR-2018, JCAI-2015, ICML-2015, ICML-2016, NeurIPS-2010, tutorials chair for UAI-2012 and workshop chair for UAI-2015 and ICML-2012; she gave several tutorials  (AAAI-1998, AAAI-2000, ICML-2010, ECML-2006) and co-organized multiple workshops at core AI conferences, including 11 workshops at NeurIPS (from 2003 to 2016), ICML-2008 and ECML-2006.