AI for Environmental Science

We welcome contributions on a wide range of topics, including but not limited to:

• AI techniques for environmental modeling, forecasting, and simulation (e.g., climate prediction, pollution dispersion, habitat modeling).

• Machine learning approaches tailored to environmental monitoring (e.g., species detection, land-use classification, remote sensing analytics).

• Multi-modal and data-fusion methods integrating satellite, sensor, and textual data for comprehensive environmental analysis.

• Explainable and trustworthy AI for supporting environmental policy-making, regulation compliance, and risk communication.

• Generative AI and large foundation models for scenario generation, ecological narrative synthesis, and scientific hypothesis formulation.

• Reinforcement learning and decision-making systems for optimizing resource management and environmental interventions.

• AI-powered early warning systems for natural disasters (e.g., floods, wildfires, earthquakes).

• Fairness, ethics, and equity considerations in AI applications for environmental sustainability and vulnerable communities.

All accepted submissions will be invited to present their work at the workshop. 

A Best Paper Award will be announced during the workshop.