On August 25 and 26, 2025, Nathalie Neptune attended the Causal Modelling and Inference Workshop, which brought together researchers working in statistics, machine learning, and social science, in Paris, France.
The workshop featured presentations on causal discovery for time series, counterfactual modeling, and causal representation learning. While much of the work is still ongoing, the event highlighted promising directions for integrating causal inference into multimodal research.
For the Integrating Geospatial Data and Legislative Text project on Hungarian forestry and fire management, the most relevant takeaways were the applications of causal time-series methods. These approaches could strengthen the project’s analysis of how forest and fire policies interact with environmental outcomes, and set the stage for future use of causal ML with satellite image time-series.
This research is supported by the Hungarian Academy of Sciences Distinguished Guest Scientists Fellowship Programme.