Conference Agenda

Brief Description and Outline:

While HFMI and Helmholtz AI provide active fora to discuss machine learning from a methodological perspective, and there are dedicated conferences on weather AI (e.g., MLESM) and remote sensing (e.g., ESA ML for EO), there are few opportunities to establish connections between domain science questions and ML methods. In this workshop, we want to explore cross-links between different environmental application areas and compartments and identify opportunities for bringing some of these together with state-of-the-art ML methods. To complement this, we will look at cutting-edge ML methods including foundation models, world models, agentic models, and discuss if these offer potential for new discoveries across environmental application areas.

Goals:

• Bring together the disparate community of Helmholtz researchers who work on environmental problems and explore the use of AI

•  Establish a forum (also beyond Helmholtz) to discuss cross-pollination from domain-specific application problems and AI methods

• Discuss domain-specific methodological aspects like spherical geometry, multi-channel images, patterns in remote sensing images and weather maps

• Bridge the current gap between remote sensing and weather AI communities and include other interesting applications

Presenters Experience:

The organizers have profound experience with organizing similar events.

Target Audience:

Researchers from Helmholtz and beyond with some experience in AI and at least one environmental application area.

Keywords:

environmental science, earth system modelling, remote sensing, weather, climate, air pollution