Information
📚 Organization | University of Florence – Department of Civil and Environmental Engineering |
📆 Period @ ESA Φ-lab | January 2026 - March 2026 |
🌍 Project @ ESA CIN | ⚠️ Project is ongoing - Generative AI for Earth System Science |
🌐 Website / Portfolio | https://gabrielebertoli.dev |
📍 GitHub | https://github.com/GabrieleBertoli |
🔨 Linkedin | http://www.linkedin.com/in/gabriele-bertoli-geoengineer |
📝 Publications | Google Scholar |
Bio
Gabriele Bertoli is a researcher in Artificial Intelligence, Hydrology, and Natural Hazard and Risk Assessment, with a strong foundation in Civil and Environmental Engineering. His academic path began at Politecnico di Milano, where he completed a Bachelor’s degree in Civil and Environmental Engineering. He then earned a Master’s degree with honours in Geoengineering from the University of Florence. After a research fellowship focused on flood risk affecting critical facilities, he began an international PhD in Civil and Environmental Engineering at the University of Florence, in co-tutelle with Technische Universität Braunschweig. During his doctoral studies, he also carried out a visiting period at Imperial College London within the Imperial Data Science Institute, joining the Data Learning Group. He has recently submitted his PhD thesis entitled “Flood Risk: An Interdisciplinary Approach Integrating Hydrology and Data Science”.
Current Role
He is currently working on Artificial Intelligence solutions for natural hazards and water resources management at the University of Florence
Areas of Expertise
Gabriele’s expertise spans key areas of hydrology and artificial intelligence, including AI-based flood forecasting, risk analysis, and data preprocessing, as well as related disciplines such as geology, geotechnics, and computer science. These skills enable him to develop models that improve the prediction and monitoring of hydrological extremes, effectively bridging hydrological science and AI. This expertise can support ESA Φ-lab CIN by contributing to the advancement of Generative AI for Earth System Science through innovative methods for extracting actionable insights from Earth-system data, while maintaining a strong connection with physical processes.
Vision for the Future
He is driven by a vision of a future in which artificial intelligence, Earth observation, and in-situ measurements are responsibly leveraged to forecast and mitigate natural-hazard impacts. His goal is to develop transparent and trustworthy forecasting and risk-assessment methods that safeguard lives and assets. By fostering collaboration across disciplines and sectors, he aims to strengthen informed decision-making and enhance societal resilience and preparedness.