About Climate Change AI
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. Since it was founded in June 2019 (and established as a US domestic non-profit on June 14, 2021), CCAI has led the creation of a global movement in climate change and machine learning, encompassing researchers, engineers, entrepreneurs, investors, policymakers, companies, and NGOs.
Our Mission
To catalyze impactful work at the intersection of climate change and machine learning.
Our Goals
- Community: To build a community of diverse stakeholders.
- Education: To guide impactful work through educational resources and programs.
- Infrastructure: To fill gaps in essential infrastructure such as funding, tools, and datasets.
- Discourse: To advance discourse and advise relevant players.
Our Guiding Principles
- On climate change: Climate change is a pressing issue with major implications for societal well-being, particularly for the world’s most disadvantaged populations. Addressing climate change requires rapid, sustained, equitable, and scientifically informed efforts in both mitigation and adaptation, in conjunction with relevant stakeholders.
- On machine learning: Machine learning is a powerful tool with wide applicability in many technological and societal applications (both positive and negative), and should be practiced in a manner consistent with its strengths, weaknesses, and limitations, as well as with climate change goals (considering both its applications and its emissions footprint).
- On machine learning for climate change: Machine learning can play an impactful role in many broader strategies for reducing and responding to climate change. At the same time, machine learning is not a silver bullet, and should serve to supplement (rather than divert attention from) other impactful actions to address climate change.
- On diversity, inclusion, and equity: Diversity, inclusion, and equity are central to the advancement of society in general, and moreover fundamental to progress in addressing climate change. Where possible, it is important that work in climate change and machine learning attempt to address the structural inequities that exist in today’s society.
People
Board of Directors

Priya L. Donti
Carnegie Mellon
CCAI Chair;
Power & Energy Lead
Power & Energy Lead

Lynn H. Kaack
Hertie School
CCAI Chair;
Public Sector Lead
Public Sector Lead

David Rolnick
McGill, Mila
CCAI Chair;
Biodiversity Lead
Biodiversity Lead

Konstantin Klemmer
University of Warwick
Communications Chair

Raphaela Kotsch
University of Zurich, ZHAW
Community Leads Chair;
Economics & Markets Lead
Economics & Markets Lead

Nikola Milojevic-Dupont
MCC Berlin, TU Berlin
Content Chair;
Buildings & Transportation Lead
Buildings & Transportation Lead

Evan D. Sherwin
Stanford University
Programs Chair
Personnel

Kameliya Petrova
Director of Projects & Partnerships

Olivia Mendivil Ramos
Cold Spring Harbor Laboratory
Director of Operations
Core Team

Dea Bankova
Reuters Graphics
Design

David Dao
ETH Zürich
Agriculture & Forestry Lead

Hari Prasanna Das
UC Berkeley
Summer School

Ján Drgoňa
Pacific Northwest National Laboratory
Community Platforms
Jesse Dunietz
Elemental Cognition
Media Relations

Simone Fobi
Columbia University
Data Lead

Meareg Hailemariam
Dakar American University of Science and Technology
Webinars

Jeremy Irvin
Stanford University
Summer School

Kai Jeggle
ETH Zürich
Community Manager

Sasha Luccioni
Mila, U. de Montréal

Tegan Maharaj
Mila, Polytechnique Montréal
Peer Review & Publishing

Ankur Mahesh
LBNL, UC Berkeley
Tutorials

Kelton Minor
UCPH, UC Berkeley
Computational Social Sciences Lead

Peetak P. Mitra
Palo Alto Research Center
Newsletter

Geneviève Patterson
VSCO
Course

Andrew Slavin Ross
NYU
Website

Mark Roth
Climate, LLC
Community Events

Maria João Sousa
IST, ULisboa
Programs Vice Chair;
Summer School
Summer School

Isabelle Tingzon
Thinking Machines Data Science
Tutorials

Kasia Tokarska
ETH Zürich
Community Leads Vice Chair;
Climate & Earth Sciences Lead
Climate & Earth Sciences Lead

Marcus Voss
Birds on Mars, TU Berlin
Wiki

Kureha Yamaguchi
University of Cambridge
Community Manager
Advisory Board

Inês Azevedo
Stanford University

Yoshua Bengio
Mila, U. de Montréal

Jennifer Chayes
UC Berkeley

Felix Creutzig
MCC Berlin, TU Berlin

Carla Gomes
Cornell University

Demis Hassabis
DeepMind

Zico Kolter
Carnegie Mellon

Konrad P. Körding
University of Pennsylvania

Claire Monteleoni
CU Boulder

Catherine Nakalembe
University of Maryland

Andrew Y. Ng
Stanford University

John C. Platt
Google AI

Tobias Schmidt
ETH Zürich

Craig Smith
Eye on AI
Former Core Team Members
- Ebude Antem Yolande Ebong
- Jessica Fan
- Natasha Jaques
- John Kieffer
- Kelly Kochanski
- Lauren Kuntz
- Alexandre Lacoste
- Wei-Wei Lin
- Felipe Oviedo
- Kris Sankaran
- Katherine Stapleton
- Anna Waldman-Brown
- Yumna Yusuf
- Sharon Zhou
Press
Releases
- Climate Change and AI: Recommendations for Government (Nov. 8, 2021): press release
- CCAI Innovation Grants program (Aug. 30, 2021): press release
- MIT Technology Review 35 Under 35 awards (Jun. 30, 2021): press release
- Paper: Tackling Climate Change with Machine Learning (Nov. 11, 2019): press release and press packet
Selected articles
- The Economist Intelligence Unit: Green Intelligence - AI could boost efforts to fight climate change (May 2021)
- Capgemini: Climate AI: How artificial intelligence can power your climate action strategy (Nov 2020)
- Forbes: Is Fusion Really Close To Reality? Yes, Thanks To Machine Learning (Apr 2020)
- CleanTechnica: Machine Learning Experts Issue Call To Arms For Climate Focus (Jan 2020)
- National Geographic: How artificial intelligence can tackle climate change (Jul 2019)
- The Verge: Here’s how AI can help fight climate change according to the field’s top thinkers (Jun 2019)
- MIT Technology Review: Here are 10 ways AI could help fight climate change (Jun 2019)
Selected podcasts and radio shows
- The Interchange: How A.I. Will Revolutionize Climate Tech (Jun 2021)
- Körber Stiftung: Der Zusammenhang von Klima und KI (Mar 2021, German)
- ASP Flashpoint: Climate and AI (Aug 2020)
- Deutschlandfunk: Künstliche Intelligenz gegen den Klimawandel (May 2020, German)
- The Interchange: Beyond Forecasting: Artificial Intelligence Is a Powerful Decarbonization Tool (Feb 2020)
- “Not Cool: A Climate Podcast” by the Future of Life Institute: Part 1 and Part 2 (Oct 2019)
- Eye on A.I. podcast: Climate Change and AI (Sep 2019)