Dec 15, 2024 · Climate Change AI is a global non-profit that catalyzes impactful work at the intersection of climate change and machine learning.

Climate Change AI (CCAI) is an organization composed of volunteers from academia and industry who believe that tackling climate change requires concerted societal action, in which machine learning can play an impactful role.

The Climate Change AI Summer School took place from June to August 2024 and included two distinct programs: a virtual program and a selective in-person program. Registrations and applications are now closed, but details of each program can be found below.

Projects in the Main Track should leverage AI or machine learning to address problems in climate change mitigation, adaptation, or climate science, or consider problems related to impact assessment and governance at the intersection of climate change and machine learning.

Abstract: The growing computational demands of artificial intelligence (AI) in addressing climate change raise significant concerns about inefficiencies and environmental impact, as highlighted by Jevons' paradox. We propose an attention-enhanced quantum physics-informed neural network (AQ-PINN) to tackle these challenges.

Connect with the Climate Change AI community, Find your next job in climate tech or new collaborators for tackling climate change with machine learning.

Jul 21, 2023 · Abstract: In response to climate change, assessing crop productivity under extreme weather conditions is essential to enhance food security. Crop simulation models, which align with physical processes, offer explainability but often perform poorly.

Apply machine learning to predict climate variables into the future and transform low-resolution outputs of climate models into high-resolution regional forecasts.

Dec 2, 2021 · An important application of climate models is to provide metrics of mean and extreme climate changes, particularly under these alternative future scenarios, as these quantities drive the impacts of climate on society and natural systems.

This workshop is part of the “Tackling Climate Change with Machine Learning” workshop series, which aims to bring together those applying ML to climate change challenges and facilitate cross-pollination between ML researchers and experts in climate-relevant fields.