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David Duvenaud is an Associate Professor at the University of Toronto, specializing in Artificial General Intelligence (AGI) governance and evaluation, as well as mitigating catastrophic risks associated with future systems. His research journey includes significant contributions to the development of deep probabilistic models, with applications in predicting and designing various elements across diverse fields. Duvenaud's academic accolades include a Ph.D. from the University of Cambridge and postdoctoral work with the Harvard Intelligent Probabilistic Systems group, where he collaborated with notable researchers. He is also a founding member of the Vector Institute and holds the Schwartz Reisman Chair in Technology and Society at the University of Toronto. His body of work highlights innovative methodologies, including Neural Ordinary Differential Equations and automated chemical design via generative models, reflecting his commitment to pushing the boundaries of machine learning. Duvenaud's current focus rests on the ethical implications of advanced AI systems and their governance, contributing to op-eds that address the socio-economic impacts of these technologies. His publications often explore and predict the interplay between AI capabilities and human agency.
Department of Sociology