Part of the TPC Seminar Series

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Biography:

Irina Rish is a distinguished Full Professor at the Université de Montréal (UdeM) and a core faculty member of MILA – Quebec AI Institute, holding prestigious positions such as Canada Excellence Research Chair and CIFAR Chair. With an academic background including MSc and PhD in AI from the University of California, Irvine, and an MSc in Applied Mathematics from Moscow Gubkin Institute, Irina leads the Autonomous AI Lab. Her extensive research career spans various AI domains, from automated reasoning to neuroscience-inspired AI. Currently, she focuses on continual learning, out-of-distribution generalization, and understanding neural scaling laws in foundation models for achieving Artificial General Intelligence (AGI). Irina actively contributes to large-scale AI projects, leading an INCITE project on Scalable Foundation Models at the Oak Ridge Leadership Computing Facility, and serves as the co-founder and Chief Science Officer of nolano.ai, a company specializing in large-scale AI model training and inference. Before joining UdeM, she worked at the IBM T.J. Watson Research Center, receiving several awards for her contributions to neuroscience and AI projects. Irina’s impressive track record includes 64 patents, over 120 research papers, and various accolades, emphasizing her significant impact on the field. Additionally, she plays a pivotal role in education, teaching courses on AI scaling and alignment while organizing the Neural Scaling & Alignment workshop series.