Mila Announces Four New Canada-CIFAR AI Chairs and One Renewal
The appointments support research on more efficient learning, adaptable robots, autonomous-system governance and human language acquisition.
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The appointments support research on more efficient learning, adaptable robots, autonomous-system governance and human language acquisition.
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The five chair decisions back research spanning neural-network optimization, robotics, governance of autonomous systems, language learning and adaptive AI agents. The appointments also reinforce the Canada-CIFAR program’s role in attracting researchers to Canada and supporting existing talent, with university-affiliated professors receiving long-term funding for research and training. The mix links technical work to deployment and policy questions, while the renewal keeps support in place for research on agents’ long-term performance.
Felix Dangel studies neural-network learning through second-order properties, including loss-landscape curvature, with the aim of improving speed, interpretability and computing efficiency.
David Meger combines 3D perception and data-efficient reinforcement learning to help robots adapt in complex real-world settings.
AJung Moon develops governance approaches for autonomous systems, while Eva Portelance uses computational models of language acquisition to inform AI architectures and cognitive-learning theory.
Four Mila academic members have been appointed Canada-CIFAR AI Chairs, while Amir-massoud Farahmand’s existing chair has been renewed. Mila announced the appointments on October 6, 2026. The program provides university-affiliated professors with long-term, dedicated funding for research and training the next generation of AI leaders in Canada.
The Canada-CIFAR AI Chairs Program is part of the Pan-Canadian Artificial Intelligence Strategy.
The program aims to recruit top AI researchers from around the world to Canada while supporting existing talent.
Mila, describing the Canada-CIFAR AI Chairs Program
The renewal goes to Amir-massoud Farahmand, an associate professor at Polytechnique Montréal and core academic member at Mila. His research examines the computational and statistical mechanisms needed to design efficient AI agents. These are systems that interact with their environment and adapt to improve their performance over time. Mila says the renewal recognizes his work on improving those agents’ long-term performance.
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