Machine learning can be a powerful tool in helping society reduce greenhouse gas emissions and adapt to a changing climate. In this discussion, we will explore opportunities and challenges in AI-for-climate, from optimizing electrical grids to monitoring crop yield, and how methodological innovations in machine learning can be driven by impactful climate-relevant problems.
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Tackling climate change with machine learning A discussion with Prof.
Monday 4 April 2022, 11:30 to 12:00
Place
En ligne
Les billets virtuels donnent accès aux conférences en rediffusion à partir du lendemain
Room
Salle Desjardins
David Rolnick
Co-Founder of Climate Change AI
Université McGill
David Rolnick is an Assistant Professor and Canada CIFAR AI Chair in the School…
David Rolnick is an Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science at McGill University and at Mila Quebec AI Institute. He is a Co-founder and Chair of Climate Change AI and serves as Scientific Co-director of Sustainability in the Digital Age. Dr. Rolnick is a former NSF Mathematical Sciences Postdoctoral Research Fellow, NSF Graduate Research Fellow, and Fulbright Scholar, and was named to the MIT Technology Review's 2021 list of "35 Innovators Under 35". He received his Ph.D. in Applied Mathematics from MIT.
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