Climate change is one of the greatest problems society has ever faced, with increasingly severe consequences for humanity. While no silver bullet, machine learning can be an invaluable tool in tackling climate change via a wide array of applications and techniques. These applications require close collaboration with diverse fields and practitioners, and many call for algorithmic innovations in machine learning. We are organizing a conference track at the Applied Machine Learning Days (AMLD) at EPFL as a forum for work at the intersection of machine learning and climate change.
AMLD is a five-day conference of talks, tutorials & workshops on applied machine learning. AMLD is organized by EPFL in Lausanne, Switzerland, from January 25 to 29, 2020.
The call for submissions of presentations and posters through the AMLD conference is now open. You can submit directly to our track by choosing it from the dropdown menu on the AMLD submission website. We invite submissions of work using machine learning to address problems in climate mitigation, adaptation, or modeling, including but not limited to the following topics:
Lynn Kaack (ETH Zürich)
Nikola Milojevic-Dupont (MCC Berlin)