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 (McGill University and Mila-Quebec AI Institute) will explore opportunities and challenges in machine learning for climate action, from designing new electrocatalysts to monitoring biodiversity. He will also consider 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.
The workshop is free and open to the public. Snacks and other refreshments will be served.
"Tackling Climate Change with Machine Learning" is the first in a year-long series of workshops on Artificial Intelligence and Climate Change, which has been organized by the Penn Program on Regulation. The series is made possible in part by funding from the Environmental Innovations Initiative. Additional co-sponsors include the Kleinman Center for Energy Policy, Center for Technology, Innovation & Competiton, Warren Center for Network and Data Sciences, and Wharton Climate Center.
For more information about the series, please visit https://pennreg.org/ai-and-climate-change.
Registration is not required, but encouraged: https://www.cvent.com/c/express/bfd1de36-6ca2-4c83-849c-6f56f439bb24.