The AI for Climate Change Bootcamp provides Stanford students an opportunity to do cutting-edge research at the intersection of AI and climate change. Students receive training from PhD students and bootcamp faculty to do interdisciplinary research on high impact problems.

Projects in the bootcamp have included work in a variety of climate-relevant subfields including (1) energy on detecting solar, wind, and oil and gas infrastructure in satellite imagery, (2) earth science on predicting methane emissions from natural wetlands, (3) deforestation on classifying the drivers of forest loss events using satellite imagery, and (4) transportation on detecting travel infrastructure in urban areas using street view and aerial imagery, and span a variety of machine learning subfields, including self-, semi-, and weakly supervised learning, active learning, and probabilistic forecasting.

Academic collaborators include faculty at Stanford University, UC Berkeley, the University of Illinois Chicago, the University of British Columbia, and the University of Oxford.

AICC bootcamp alumni have pursued PhD programs at Stanford, Cambridge, and Harvard University, and assumed industry roles at OpenAI, Google X, Meta Research, and Microsoft Research.

Teaching Team

Jeremy Irvin

Andrew Ng

Climate Change Faculty

Rob Jackson

Ram Rajagopal

Sara Knox

Daniel Rodriguez

Gavin McNicol

Chris Field

Jackelyn Hwang

Peter Kitanidis

Etienne Fluet-Chouinard

Zutao Yang

Duncan Watson-Parris

Nonprofit and Industry Collaborators

Kemen Austin

Jack Kelly

David Gagne

Ritesh Gautam

Mark Omara

Kelsey Meisenhelder

Kyle Story

Rose Rustowicz

Cooper Elsworth


The AICC bootcamp is an intense two-quarter program where students work on high-impact research problems at the intersection of AI and climate change. Students work closely with PhD students in Professor Andrew Ng's lab and with faculty members in climate change-related fields. Students also collaborate with climate change experts from industry.

The program includes teaching team and guest lectures on machine learning methods and tools and their application to climate change, as well as reading groups covering state-of-the-art research at the intersection of AI and climate change. Students learn about a variety of AI topics relevant to climate change with an emphasis on remote sensing applications.


Students with a background in artificial intelligence are encouraged to apply. Our group’s primary focus is doing academic work that makes an impact--that is, we emphasize doing work that directly helps mitigate and adapt to climate change--so please apply only if you similarly have an impact-oriented mindset.

Applications for the Summer 2024 bootcamp are now open. Students may have the option to a second quarter in the Fall.

  • Regular Applications due May 31st, 2024 at 11:59p PST.
  • Late Applications due June 14th, 2024 at 11:59p PST. Apply early to give yourself enough time to prepare for the interview.
  • Rolling interviews and selections through June 21st, 2024.
  • Bootcamp starts June 24th, 2024.
Apply Now

Prerequisites and Commitment

The bootcamp is suited for students who have taken machine learning and software engineering courses. Students will be able to apply and sharpen these skills, developing machine learning solutions to challenging problems with the mentorship of CS PhD students and in collaboration with faculty and industry experts. Students have the opportunity to take a deep dive into climate change and co-author a research paper. We expect students to have:

  • Taken machine learning courses (CS229/CS230/CS224N/CS231N or equivalent).
  • Proficiency in software engineering (CS106B or equivalent), computer systems (CS107 or equivalent), and have done Python programming.
  • The bootcamp as their primary academic engagement (30 hours per week) outside of 1 or 2 courses. We encourage students to sign up for research credits (CS 199, CS 399, etc).

Bootcamp Cohorts

Climate Change Bootcamp Winter 2023-2024

Riya Dulepet

Emily Liu

Santino Ramos

Joyce Chen

Ines Dormoy

Jinyoung Kim

Apoorva Dixit

Climate Change Bootcamp Winter 2022-2023

Mabel Jiang

Ishan Sabane

Li Tian

Benjamin Yan

Ethan Hellman

Pratyush Muthukumar

Senem Isik

Pura Peetathawatchai

Climate Change Bootcamp Fall 2022-2023

Joanne Zhou

Amol Singh

Haijing Zhang

Manuka Stratta

Lucas Tao

Ji Hun Wang

Yuzu Ido

Spencer Paul

Climate Change Bootcamp Spring 2021-2022

Quentin Hsu

Maya Srikanth

Eric Frankel

James Zheng

Daniella Hacco Grimberg

Felipe Godoy

Brian Hill

Ayush Singla

Climate Change Bootcamp Winter 2021-2022

Beri Kohen Behar

Lyna Kim

Muhammad Ahmed Chaudhry

Ha Tran

Sahil Tadwalkar

Climate Change Bootcamp Fall 2021-2022

Nicholas Lui

Bryan Zhu

Timothy Dai

Suhas Chundi

Yuntao Ma

Langston Nashold

Jimmy Le

Climate Change Bootcamp Summer 2021

Jake Silberg

Matt Kolodner

Sarthak Kanodia

Climate Change Bootcamp Spring 2020-2021

Gil Kornberg

Raghav Samavedam

Sergio Charles

Collin Kwon

Benjamin Liu

Climate Change Bootcamp Winter 2020-2021

Lyron Co Ting Keh

Jake Taylor

Sonia Chu

Mauricio Wulfovich

Chris Rilling

Andrew Yang

Climate Change Bootcamp Fall 2020-2021

Irena Gao

Sam Masling

Erfan Rostami

Tatiana Wu

Andrew Hwang

Julie Fang

JK Hunt

Michelle Bao

Eric Matsumoto

Climate Change Bootcamp Summer 2020

Jared Isobe

Eric Zeng

Climate Change Bootcamp Spring 2019-2020

Andrew Ying

Heejung Chung

Avoy Datta

Tai Vu

Jenny Yang

Tiger Sun

Climate Change Bootcamp Winter 2019-2020

Shawn Zhang

Sasankh Munukutla

Christopher Cross

Climate Change Bootcamp Fall 2019-2020

Sonja Johnson-Yu

Eric Zelikman

Cooper Raterink

Neel Ramachandran

Climate Change Bootcamp Summer 2019

Neethu Renjith

Jiyao Yuan

Climate Change Bootcamp Spring 2018-2019

Fred Lu

Andrew Kondrich

Vincent Liu

Jabs Aljubran

Eva Zhang

Will Deaderick

We invite you to join the forefront of AI for climate change

Apply Now