We rethink how sensing technologies are designed, deployed, and combined. By leveraging advances in low-cost hardware (such as drones, connected sensors, and compact optical and infrared instruments) and combining them with remote sensing data, we create integrated sensing systems that are flexible, scalable, and accessible.

Artificial Intelligence is transforming how we interpret the growing volume of Earth Observation and in-situ data; but insight without understanding is not enough. We develop AI solutions that prioritize transparency, interpretability, and robustness. This focus on explainability helps reduce bias, improves reliability, and builds trust, enabling AI systems that can be confidently applied, transferred to new contexts, and adopted at scale.

We design computational frameworks that turn complex environmental data into reliable, ready-to-use information. Our work supports sustainable management of natural resources, ecosystem protection, and food security by integrating large volumes of open Earth Observation data with advanced environmental models.