Spotlight paper at NeurIPS workshop organized by Climate Change AI

This December, I will participate as the first author of a paper at the “Tackling Climate Change with Machine Learning” workshop, organized by Climate Change AI as part of NeurIPS 2022.

The paper is titled “Personalizing Sustainable Agriculture with Causal Machine Learning”. I am glad to share that it was selected for a spotlight presentation (top 10% of accepted papers).

In this work, we propose the use of causal machine learning for understanding the impact of sustainable agriculture in terms of local conditions. In that way, we can efficiently uplift green metrics and contribute to the sustainable intensification of agriculture. Here, we focus on understanding how much is Soil Organic Carbon driven by eco-friendly management practices.

As the Earth Observation industry scales up, data of higher volume and quality will keep becoming available, including data on emissions as well as on soil organic carbon. Machine Learning methods are already highly efficient in dealing with big data.

Combining the best of both worlds and explicitly incorporating the fundamental concept of causation in it, we believe that our idea can scale with data capabilities and assist the climate-smart policies of the future.

During the past 3 years, the “Tackling Climate Change with Machine Learning” workshop has been part of the largest AI conferences of the world, including NeurIPS, ICML and ICLR. It features short papers with self-published proceedings, and attracts a large, diverse group of attendees from both industry and academia. This year, 112 papers were accepted, including works from MIT, Google, Microsoft and others.