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

Co-Founder CCAI Chair

Co-Founder CCAI Chair Public Sector Co-Lead

Co-Founder CCAI Chair

Rasika Bhalerao

Northeastern University

Communications Chair Newsletter

Kameliya Petrova

Community Leads Chair

Programs Chair Community Events

Staff

Maria João Sousa

Executive Director

Research Scientist (Data Gaps)

Yale School of the Environment

Administrative Assistant

Educational Events Coordinator

Research Scientist (Data Gaps)

Core Team

Cambridge Institute for Sustainable Leadership and Cotopaxi

Industry Events

Community Events

Olalekan Akintande

University of Ibadan

Community Events

Biodiversity Lead

Ashwin Bhanot

Blog

National Centre for Atmospheric Science

Agriculture & Forestry Lead

Hari Prasanna Das

Media Relations

University of Bristol

Microsoft AI for Good Research Lab

Jade Eva Guisiano

ISEP, Polytechnique, UNEP

Meareg Hailemariam

Dakar American University of Science and Technology

Stanford University

Summer School Course

University of Toronto

Communications Vice Chair Volunteer Matching

Community Events

Konstantin Klemmer

Social Media Lead

Raphaela Kotsch

University of Zurich, ZHAW

Economics & Markets Lead

Fero Labs, Columbia University

Entrepreneurship Lead

Shiva Madadkhani

Nikola Milojevic-Dupont

MCC Berlin, TU Berlin

Yazid Salahudeen Mikail

Ahmadu Bello University

Programs Vice Chair Community Events

Panayiotis Moutis

City College of New York

Power & Energy Lead

Tejasri Nampally

Community Platform Lead

Arthur Ouaknine

McGill University, Mila

Amanda Sessim Parisenti

National University of Singapore

Community Platform Lead

Andrew Slavin Ross

Intercontinental Exchange

Oxford Open Infrastructure and Health

Public Health Lead

Daniel Spokoyny

Carnegie Mellon

Isabelle Tingzon

UNICEF, The World Bank, GFDRR

Climate & Earth Sciences Lead

Birds on Mars, TU Berlin

Buildings & Transportation Lead

Community Events

Gina Wong

Johns Hopkins

Data

Advisory Board

Stanford University

Mila, U. de Montréal

Jennifer Chayes

MCC Berlin, TU Berlin

Cornell University

Carnegie Mellon

Konrad P. Körding

University of Pennsylvania

Claire Monteleoni

Catherine Nakalembe

University of Maryland

Stanford University

Former Core Team Members

Press

Releases

2022-2023 Innovation Grants Winners (June 26, 2024)
CCAI Innovation Grants 2023 (Nov. 4, 2022)
2021-2022 Innovation Grants Winners (May 5, 2022)
Climate Change and AI: Recommendations for Government (Nov. 8, 2021)
CCAI Innovation Grants 2022 (Aug. 30, 2021)
MIT Technology Review 35 Under 35 awards (Jun. 30, 2021)
Paper: Tackling Climate Change with Machine Learning (Nov. 11, 2019)
- Press packet

Selected articles

Popular Science: AI can help fight climate change—but it can also make it worse (May 2022)
Der Spiegel: How High-Tech Tools Are Helping Combat Climate Change (Sep 2021)
pv magazine: Climate Change AI unveils US$2 million grant program (Aug 2021)
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

WiDS Podcast: Priya Donti | Using AI to Fight the Climate Crisis (Jan 2023)
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)