Tackling climate change with machine learning: An opportunity for application-driven innovation
Date/Time
Date(s) - April 24, 2025
2:00 PM - 3:00 PM
Date/Time
Date(s) - April 24, 2025
2:00 pm - 3:00 pm
Location
CREATE Tower
Categories No Categories
Date: Thursday, 24 April 2025
Time: 2pm – 3pm (2pm – 2:45pm: Talk; 2:45pm – 3pm: Q&A)
Venue: CREATE Summit Room L16, CREATE Tower
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Abstract: Machine learning is increasingly being called upon to help address climate change, from processing satellite imagery to modeling Earth systems. Such settings represent an important frontier for machine learning innovation, where traditional paradigms of large, general-purpose datasets and models often fall short. In this talk, we show how an application-driven paradigm for algorithm design can respond to problem-specific goals and incorporate relevant domain knowledge. We introduce novel techniques that leverage the structure of the problem to improve accuracy and usability across applications, including monitoring land use with remote sensing, designing chemical catalysts for the energy transition, and downscaling climate data.
About the speaker: 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 and co-lead of the Global Center on AI and Biodiversity Change (ABC). Dr. Rolnick is a Sloan Research Fellow and an AI2050 Early Career Fellow and was named to the MIT Technology Review’s 2021 list of “35 Innovators Under 35” for his work in building the field of AI and climate change. He received his Ph.D. in Applied Mathematics from MIT and is a former Fulbright Scholar, NSF Graduate Research Fellow, and NSF Mathematical Sciences Postdoctoral Research Fellow.
