Machine learning, deep learning, neuroscience
Her current research interests include continual lifelong learning, optimization algorithms for deep neural networks, sparse modeling and probabilistic inference, dialog generation, biologically plausible reinforcement learning, and dynamical systems approaches to brain imaging analysis. Before joining UdeM and MILA 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 80 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, NIPS-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 NIPS (from 2003 to 2016), ICML-2008 and ECML-2006.
Irina Rish is an Associate Professor in the Computer Science and Operations Research department at the Université de Montréal (UdeM) and a core member of MILA – Quebec AI Institute. She holds MSc and PhD in AI from University of California, Irvine and MSc in Applied Mathematics from Moscow Gubkin Institute. Dr. Rish’s research focus is on machine learning, neural data analysis and neuroscience-inspired AI.
For more information…
- 30-03-2020 Mobilisation des chercheurs en intelligence artificielle pour endiguer la pandémie du coronavirus
- 10-12-2019 Nomination de quatre chercheurs de l’UdeM aux chaires en IA Canada-CIFAR
- 30-08-2020 IA: une route longue et sinueuse
- 30-08-2020 Une sommité en intelligence artificielle choisit Montréal
- 05-09-2020 Artificial intelligence expert moves to Montreal because it's an AI hub
- 10-09-2020 Research into AI, Neuroscience, Psychology Aims to Make AI Less Artificial
- 31-10-2020 Irina Rish, de l’Ouzbékistan à Montréal
- 11-02-2021 Irina Rish s'exprime sur le rôle des femmes de science
Affiliations and responsabilities
Teaching and supervision
Publications and presentations
- Computer Science
Areas of expertise
- Deep learning
- Data science
- Brain–computer interface
- Neural Networks
- Model Building
- Probabilistic models