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Climate Change AI Newsletter

With this email, we’re launching the CCAI newsletter, focused on work at the intersection of climate change and machine learning. Below we have listed some updates and opportunities. We are particularly excited to announce the call for submissions to the CCAI Workshop at NeurIPS 2019! Moving forward, we encourage input from the community by email (climatechangeai@gmail.com) and our soon-to-be-created discussion board.

 

Besides this newsletter, we are developing other resources for collaboration on climate change and machine learning, which we will announce through our website and in this newsletter. Stay tuned!

Climate Change AI workshop at NeurIPS

Announcing the workshop “Tackling Climate Change with Machine Learning” at NeurIPS.

 

When: December 13 or 14, 2019

Where: Vancouver, Canada

Submission deadline: September 11, 11:59 PM Pacific Time

Details: https://www.climatechange.ai/NeurIPS2019_workshop.html

Please share widely!

News, recent work, and climate impact
 

The recent CCAI workshop at ICML attracted great work on a wide range of problems related to climate change. You can find all these papers and more here.


We’d like to specifically highlight and congratulate the workshop award winners:

 

Duncan Watson-Parris, Sam Sutherland, Matthew Christensen, Anthony Caterini, Dino Sejdinovic and Philip Stier (University of Oxford) won the best paper award for their work on “Detecting anthropogenic cloud perturbations with deep learning”. pdf

 

Volodymyr Kuleshov (Stanford University) won an honorable mention in the Deployed track for their paper, “Towards a sustainable food supply chain powered by artificial intelligence”. video

 

Neel Guha (Carnegie Mellon University) and Zhecheng Wang and Arun Majumdar (Stanford University) earned an honorable mention in the Research track for their work on “Machine learning for AC optimal power flow”. pdf

 

Christian Schroeder and Thomas Hornigold (University of Oxford) won an honorable mention in the Ideas track for their concept of “Stratospheric aerosol injection as a deep learning reinforcement problem”. pdf

 

Calls for collaboration

 

Laure Zanna (University of Oxford and New York University) is interested in establishing collaborations to improve climate predictions (especially coastal sea level, marine heat waves, etc.) or to improve models and their parameterizations. She is working closely with developers of climate models in the US and UK. If you are looking for collaborators working on climate and earth sciences, please get in touch. 


Haewon McJeon (Joint Global Change Research Institute at Pacific Northwest National Laboratory) is seeking collaborators with machine learning expertise. He has generated ~100k scenarios modeling the impacts of different climate futures using integrated assessment models (IAMs), and would like to find ML tools to make good use of this dataset - for example, by identifying the most effective decarbonization strategies for different countries and institutions. If this problem intrigues you, please get in touch.

Opportunities


AI for Earth grants: The next deadline is on October 7, 11:59 PM Pacific Time. Apply here.

Applied Machine Learning Days January 25-29, 2020, at EPFL, Switzerland: Call for tracks and workshops. Find out more.

Jobs and open positions

 

Academia:
 

Postdoctoral Researcher in Climate/Ocean Physics and Machine Learning in the Mathematics Department at NYU Courant. Details here.

Master’s thesis opportunity at ETH Zürich: Classifying patents with ML for clean energy innovation policy. Details here.


Industry:

Natural Language Processing Engineer with Tomorrow Co. in Copenhagen, Denmark. Details here.
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Dates and deadlines reported in this newsletter may change, and CCAI is not responsible for any inadvertent inaccuracies.

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