EEPS 1720 / DATA 1720: Tackling Climate Change with Machine Learning
Course Website [Spring 2023]
This course will explore recent work that leverages machine learning (ML) as a tool for tackling climate change, with a focus on climate science and climate adaptation. We will discuss how modern machine learning can be used to assess, understand and respond to projected climate extremes, natural disasters, and environmental change. The target audience for this course is advanced undergraduate students or graduate students who are interested in using ML and AI to address high-impact global issues. Students will read and discuss recent research papers on ML for Climate and complete an original project as a member of a multidisciplinary team.
Climate themes may include: Climate models and predictions; Extreme weather and natural disasters; Farms and forests; Oceans and marine ecosystems; Climate misinformation.
Machine learning topics may include: Physics-informed learning and emulators; Explainable AI; Uncertainty quantification; Image super-resolution; Graph neural networks, Policy optimization.