Tackling Climate Change with Machine Learning
Tackling Climate Change with Machine Learning


Climate change is one of the greatest challenges facing humanity, and data scientists may wonder how we can help. In this talk, we will see how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we explore high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. These problems lead to exciting research questions as well as promising business opportunities.


David Rolnick is an NSF Mathematical Sciences Postdoctoral Research Fellow at the University of Pennsylvania. His research focuses on the mathematical foundations of deep learning. David is co-founder of Climate Change AI, an organization dedicated to furthering applications of machine learning that meaningfully address the climate crisis.

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