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SUMMARY:Machine Learning in Climate Action - David Rolnick\, McGill Univer
 sity
DTSTART:20230127T130000Z
DTEND:20230127T140000Z
UID:TALK183293@talks.cam.ac.uk
CONTACT:Madeline Lisaius
DESCRIPTION:Machine learning (ML) can be a useful tool in helping society 
 reduce greenhouse gas emissions and adapt to a changing climate. In this t
 alk\, we will explore opportunities and challenges in ML for climate actio
 n\, from optimizing electrical grids to monitoring crop yield\, with an em
 phasis on how to incorporate domain-specific knowledge into machine learni
 ng algorithms. We will also consider ways that ML is used in ways that con
 tribute to climate change\, and how to better align the use of ML overall 
 with climate goals.\n\nDavid 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 Chang
 e AI and serves as Scientific Co-director of Sustainability in the Digital
  Age. Dr. Rolnick received his Ph.D. in Applied Mathematics from MIT. He i
 s a former NSF Mathematical Sciences Postdoctoral Research Fellow\, NSF Gr
 aduate Research Fellow\, and Fulbright Scholar\, and was named to the MIT 
 Technology Review's 2021 list of "35 Innovators Under 35."
LOCATION:FW 11\, Willam Gates Hall. Zoom link: https://cl-cam-ac-uk.zoom.u
 s/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&amp\;from=addon 
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