Tackling Climate Change with Machine Learning
Workshop at International Conference on Machine Learning (ICML 2021)
Virtual: July 23rd or 24th, 2021
Workshop website: https://www.climatechange.ai/events/icml2021.html
Submission deadline: May 31st
Mentorship application deadline: April 28th
Informational webinars: April 23 (1:30 PM ET) and April 27 (9 AM ET) (More info)
We invite submissions of short papers using machine learning to address climate change. All machine learning techniques are welcome, from kernel methods to deep learning. Each submission should clearly illustrate why the application has (or could have) a pathway to impact regarding climate change. We highly encourage submissions that make their data publicly available.
Submissions are non-archival, and do not preclude future publication.
We strongly encourage authors to consider applying for our mentorship program (applications due April 28th), which will pair authors with mentors having complementary expertise. Applications to participate as a mentor are also open; we invite those from academia, industry, government, and beyond to apply. Please see the workshop website for application instructions and more details on the program.
Additional details on submissions:
Potential topics for submissions include but are not limited to the following areas of climate change mitigation, adaptation, and climate science:
Buildings and cities
Behavioral and social science
Carbon capture and sequestration
Climate finance and economics
Disaster prediction, management, and relief
Earth science and monitoring
Ecosystems and natural systems
Forestry and other land use
Heavy industry and manufacturing
Power and energy systems
Accepted submissions will be invited to give virtual poster presentations, of which some will be selected for spotlight talks.
Submissions are limited to 4 pages for the Papers Track (work that is in progress, published, and/or deployed), and 3 pages for the Proposals Track (detailed descriptions of ideas for future work or early-stage results), with additional pages permitted for references and appendices. All submissions *must* explain why the work has (or could have) positive impacts regarding climate change, and why the machine learning methods involved are needed.
We will be holding informational webinars with advice on how to prepare a successful workshop submission, and as an opportunity to ask questions regarding the mentorship program:
Friday, April 23rd at 1:30 PM Eastern Time / 6:30 PM London time
Tuesday, April 27th at 9:00 AM Eastern Time / 2:00 PM London time / 9:00 PM Beijing Time
Please see the workshop website for further details on the workshop.
Hari Prasanna Das (UC Berkeley)
Kasia Tokarska (ETH Zurich)
Maria João Sousa (IST, ULisboa)
Meareg Hailemariam (DAUST)
David Rolnick (Mila, McGill)
Xiaoxiang Zhu (TU Munich)
Yoshua Bengio (Mila, UdeM)