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 Public Sector Co-Lead

Co-Founder CCAI Chair

Maria João Sousa

IST, ULisboa, Cornell Tech

CCAI Chair Incoming Executive Director Summer School

Konstantin Klemmer

Microsoft Research

Communications Chair

Olivia Mendivil Ramos

OneThree Biotech

Birds on Mars, TU Berlin

Community Leads Chair Buildings & Transportation Lead

Staff

Co-Founder Executive Director

Kameliya Petrova

Consulting Director: Projects & Partnerships

via Future Earth International

Educational Events Coordinator

Research Scientist (Data Gaps)

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

Rasika Bhalerao

Northeastern University

Communications Vice Chair Newsletter

National Centre for Atmospheric Science

Agriculture & Forestry Lead

Hari Prasanna Das

AAAS Science & Technology Policy Fellowship

Media Relations

Microsoft AI for Good Research Lab

Newsletter Blog

Jade Eva Guisiano

ISEP, Polytechnique, UNEP

Meareg Hailemariam

Dakar American University of Science and Technology

Stanford University

Summer School Course

Volunteer Matching

Community Events

Raphaela Kotsch

University of Zurich, ZHAW

Economics & Markets Lead

Fero Labs, Columbia University

Entrepreneurship Lead

Shiva Madadkhani

Community Events

Nikola Milojevic-Dupont

MCC Berlin, TU Berlin

Content Vice Chair

Community Events

Panayiotis Moutis

City College of New York

Power & Energy Lead

Arthur Ouaknine

McGill University, Mila

Amanda Sessim Parisenti

Andrew Slavin Ross

Programs Vice Chair Community Events

Northeastern University

Evan D. Sherwin

Stanford University

Daniel Spokoyny

Carnegie Mellon

Isabelle Tingzon

Thinking Machines Data Science

Community Leads Vice Chair Climate & Earth Sciences Lead

Community Events

Gina Wong

Johns Hopkins

Data

Kureha Yamaguchi

University of Cambridge

Community Platform Lead

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

Dea Bankova
Zikri Bayraktar
Ashesh Chattopadhyay
Ján Drgoňa
Ebude Antem Yolande Ebong
Jessica Fan
Soledad Galli
Natasha Jaques
John Kieffer
Kelly Kochanski
Lukas Kondmann
Lauren Kuntz
Alexandre Lacoste
Wei-Wei Lin
Tegan Maharaj
Ankur Mahesh
Kelton Minor
Peetak P. Mitra
Felipe Oviedo
Geneviève Patterson
Kris Sankaran
Katherine Stapleton
Anna Waldman-Brown
Sharon Xu
Yumna Yusuf
Sharon Zhou

Press

Releases

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)