Tackling Climate Change with Machine Learning

September 21, 2023
Machine learning can be a useful tool in helping society reduce greenhouse gas emissions and adapt to a changing climate. In this workshop, Prof. David Rolnick explores opportunities and challenges in machine learning for climate action, from designing new electrocatalysts to monitoring biodiversity. He also considers how machine learning is used in ways that contribute to climate change, and how to better align the use of machine learning overall with climate goals.
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 also is the co-founder and chair of Climate Change AI, a non-profit that aims to catalyze a global movement at the intersection of climate change and machine learning, encompassing researchers, engineers, entrepreneurs, investors, policymakers, industry, and NGOs. And Prof. Rolnick serves as Scientific Co-director of Sustainability in the Digital Age, a think tank at Concordia University. Recently, he was named to the MIT Technology Review’s list of “35 Innovators Under 35” working in machine learning and climate change. And previously, he was an NSF Mathematical Sciences Postdoctoral Research Fellow at the University of Pennsylvania.
This event is part of the 2023-2024 Workshop Series, AI and Climate Change: Global Sustainability in an Era of Artificial Intelligence, organized by the Penn Program on Regulation. Co-sponsors include the Environmental Innovations Initiative, Kleinman Center for Energy Policy, Center for Technology, Innovation & Competition, Warren Center for Network and Data Sciences, and Wharton Climate Center.