The focus of this track is on applying machine learning to help address climate change, encompassing both mitigation (reducing the severity of climate change) and adaptation (preparing for unavoidable consequences).
Specifically, the aim is to:
- Showcase high-impact applications of machine learning to climate change mitigation and adaptation.
- Provide a platform to connect researchers and entrepreneurs who are working in this space.
- Inspire a discussion about challenges and opportunities for machine learning to have an impact on climate action.
Application domains involved in climate change mitigation include energy, transportation, buildings, industry, land use, and CO2 removal, while those for adaptation include climate modeling, extreme event prediction/response, and resilience to societal impacts. We also consider applications of machine learning to policy analysis, tools for individual action, education, and finance.