Machine Learning Challenges in the Fight for Social Good - the Covid-19 Case

Yoshua Bengio / University of Montreal

Abstract: This talk outlines two Mila projects aimed at fighting the Covid-19 pandemic which are part of Mila's AI for Humanity mission. The first one is about discovering antivirals, either via repurposing several existing drugs using graph neural networks or via discovering new drug-like molecules using reinforcement learning and docking simulations to search in the molecular space. The second project is about using machine learning to provide early warning signals to people who are contagious -- especially if they don't realize that they are -- by exchanging information between phones of users who have had dangerous contacts with each other. This extends digital contact tracing by incorporating information about symptoms, medical condition and behavior (like wearing a mask) and relies on a sophisticated epidemiological model at the individual levels in which we can simulate different individual-level and society-level strategies.

Bio: Yoshua Bengio is Professor in the Computer Science and Operations Research departments at U. Montreal, founder and scientific director of Mila and of IVADO. He is a Fellow of the Royal Society of London and of the Royal Society of Canada, has received a Canada Research Chair and a Canada CIFAR AI Chair and is a recipient of the 2018 Turing Award for pioneering deep learning, is an officer of the Order of Canada, a member of the NeurIPS advisory board, co-founder and member of the board of the ICLR conference, and program director of the CIFAR program on Learning in Machines and Brains. His goal is to contribute to uncovering the principles giving rise to intelligence through learning, as well as favour the development of AI for the benefit of all.

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