Information
📚 Organization | RAMO Earth |
📆 Period @ ESA Φ-lab | October 2026 - April 2027 |
🌍 Project @ ESA CIN | ⚠️ Project is ongoing - Learning Water Surface Elevation in River Networks from Hypersparse Satellite Altimetry |
📍 GitHub | |
📝 Publications |
Bio
I am Federico Ferlito, a machine learning and remote sensing researcher focused on Earth Observation for environmental modeling. With a BSc and MSc in Artificial Intelligence from the University of Groningen, I specialize in deep learning, computer vision, and turning satellite data into operational products for restoration and monitoring.
Current Role
My research focuses on using machine learning to reconstruct water surface elevation across river networks from sparse satellite data. Satellite altimeters capture water levels only at limited track intersections, leaving significant data gaps. To address this, we apply deep learning techniques to interpolate missing observations across river systems, ensuring that the estimated water levels remain consistent with natural river flow.
Areas of Expertise
My expertise spans deep learning for Earth Observation, satellite data analysis, and scalable geoscience data processing. At ESA Φ-lab, I contribute to ML models that reconstruct daily water-surface elevation across river networks using sparse satellite altimetry.
Vision for the Future
I aim to develop continuous, physics-informed models that reliably fill environmental data gaps with quantifiable uncertainty, making Earth Observation actionable for decision-makers and local communities.
Project as CIN Researcher
Coming Soon