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 interdiscplinary research on high impact problems.

Projects in the bootcamp have included work in (1) energy on automated detection of energy infrastructure in satellite imagery, (2) climate science on predicting methane emissions from natural wetlands, and (3) deforestation on classifying the drivers of forest loss events using satellite imagery.

Teaching Team

Jeremy Irvin

PhD Student

Hao Sheng

PhD Student

Sharon Zhou

PhD Student

Andrew Ng

Professor

Climate Change Faculty

Rob Jackson

Professor

Ram Rajagopal

Professor

Sara Knox

Professor

Daniel Rodriguez

Professor

Gavin McNicol

Postdoc

Etienne Fluet-Chouinard

Postdoc

Zutao Yang

Postdoc

Nonprofit Collaborators

Kemen Austin

RTI International

Jack Kelly

Open Climate Fix

David Gagne

NCAR

Mikaela Weisse

World Resources Institute

Christy Slay

The Sustainability Consortium

Ritesh Gautam

EDF

Mark Omara

EDF

Industry Collaborators

Kyle Story

Descartes Labs

Rose Rustowicz

Descartes Labs

Cooper Elsworth

Descartes Labs

Program

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 earth science, energy, and urban planning. Students also collaborate with climate change experts from industry.

Applications

Students with a background in artificial intelligence are encouraged to apply.

Applications for the Fall+Winter 2020 bootcamp have closed.

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 (CS107 or equivalent), and have done Python programming.
  • The bootcamp as their primary academic engagement (20-30 hours per week in lab) outside of 1 or 2 courses. We encourage students to sign up for research credits (CS 199, CS 399 etc).

Past Bootcamp Cohorts

Climate Change Bootcamp Fall 2020-2021

Irena Gao

BS Student

Sam Masling

MS Student

Erfan Rostami

BS Student

Tatiana Wu

MS Student

Andrew Hwang

BS Student

Julie Fang

MS Student

JK Hunt

MS Student

Michelle Bao

BS Student

Eric Matsumoto

MS Student

Climate Change Bootcamp Summer 2020

Jared Isobe

BS Student

Eric Zeng

BS Student

Climate Change Bootcamp Spring 2019-2020

Andrew Ying

BS Student

Heejung Chung

BS Student

Avoy Datta

MS Student

Tai Vu

BS Student

Jenny Yang

BS Student

Tiger Sun

BS Student

Climate Change Bootcamp Winter 2019-2020

Shawn Zhang

BS Student

Sasankh Munukutla

BS Student

Christopher Cross

BS Student

Climate Change Bootcamp Fall 2019-2020

Sonja Johnson-Yu

MS Student

Eric Zelikman

BS Student

Cooper Raterink

MS Student

Neel Ramachandran

MS Student

Climate Change Bootcamp Summer 2019

Neethu Renjith

MS Student

Jiyao Yuan

MS Student

Climate Change Bootcamp Spring 2018-2019

Fred Lu

MS Student

Andrew Kondrich

BS Student

Vincent Liu

BS Student

Jabs Aljubran

MS Student

Eva Zhang

BS Student

Will Deaderick

MS Student

We invite you to join the AI revolution in climate change