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.
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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 Winter+Spring 2023-2024 bootcamp are now open.
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:
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.
Apply NowThe 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 Winter+Spring 2023-2024 bootcamp are now open.
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:
The AI for Healthcare Bootcamp offers Stanford students an unique chance to engage in advanced research at the intersection of AI and healthcare. Students collaborate closely with Postdocs, PhD students from Professor Andrew Ng's lab, the AIMI Center, and faculty members in medicine. We are proud to share that our bootcamp alumni have pursued PhD programs at institutions including MIT, Stanford, UW; led industry efforts at Google Brain, Apple Health, Microsoft Research, Tesla AI; and started AI startups including Valar Labs and Wispr AI. Learn more about the history of AIHC bootcamp here.
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 postdocs and PhD students and in collaboration with medical faculty. Students have the opportunity to take a deep dive into healthcare and co-author a research paper. We expect students to:
Applications for Fall 2023 is closed. Please check back in Winter/Spring 2024 for the next application cycle.
The AI for Healthcare Bootcamp offers Stanford students an unique chance to engage in advanced research at the intersection of AI and healthcare. Students collaborate closely with Postdocs, PhD students from Professor Andrew Ng's lab, the AIMI Center, and faculty members in medicine. We are proud to share that our bootcamp alumni have pursued PhD programs at institutions including MIT, Stanford, UW; led industry efforts at Google Brain, Apple Health, Microsoft Research, Tesla AI; and started AI startups including Valar Labs and Wispr AI. Learn more about the history of AIHC bootcamp here.
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 postdocs and PhD students and in collaboration with medical faculty. Students have the opportunity to take a deep dive into healthcare and co-author a research paper. We expect students to:
Applications for the Winter+Spring 2023-2024 bootcamp are now open.
