Papers
Work that is in progress, published, and/or deployed; must include experimental or theoretical validation and a clear pathway to climate impact. Limited to four pages (references not counted).
Machine Learning/CORE Unranked
TCCML @ NeurIPS 2026
Tackling Climate Change with Machine Learning: workshop at NeurIPS 2026
The TCCML @ NeurIPS 2026 workshop brings together machine learning researchers and climate experts to advance climate mitigation, adaptation, and science through innovative ML applications. The theme, 'Fostering Ground-Up Innovation in AI and Climate,' emphasizes community-driven, application-specific solutions such as open-source tools, interdisciplinary collaborations, and practical impact pathways.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Proposals
Early-stage ideas for future work; must justify the problem's importance, inadequacy of current methods, proposed approach, and pathway to climate impact. Limited to three pages (references not counted).
Tutorials
Executable notebook tutorials demonstrating ML tools for climate challenges; must include learning outcomes, requirements.txt, and be 80% complete by August 29, 2026, with a final version due October 15, 2026.
Research areas in scope
01
Application Areas
Agriculture and foodBehavioural and social scienceBuildingsCarbon capture and sequestrationCities and urban planningClimate finance and economicsClimate justiceClimate science and climate modelingDisaster management and reliefEarth observations and monitoringEarth scienceEcosystems and biodiversityExtreme weatherForestry and other land useHealthHeavy industry and manufacturingLocal and indigenous knowledge systemsMaterials science and discoveryOceans and marine systemsPower and energy systemsPublic policySocietal adaptation and resilienceSupply chainsTransportation
Policies worth checking twice
- Submissions must be double-blind; anonymize all identifying information.
- All submissions must use the official NeurIPS-style LaTeX template.
- Submissions must explain the pathway to positive climate impact.
- Authors are required to disclose if they used LLMs during writing, and must not share CCAI website content with LLMs.
- Submissions are non-archival and do not preclude future publication.
- Previously published work may be submitted under certain circumstances (see FAQ).
- Reciprocal reviewing: Authors with two or more prior accepted TCCML or related venue papers must nominate at least one eligible author to review.
- Tutorial submissions must include an executable notebook and a requirements.txt file for reproducibility.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026