About

He is a geologist with a degree in Geological and Geophysical Sciences and is currently a PhD Candidate in Geotechnologies at the University of Bari, within the Department of Earth and Geoenvironmental Sciences, in collaboration with Yale University.

His research focuses on large-scale geospatial modeling of landslide susceptibility using machine learning approaches on High-Performance Computing (HPC) systems. His work emphasizes the integration and data fusion of heterogeneous satellite datasets to assess natural hazard susceptibility at the global scale. In parallel, he works as a freelance instructor with Spatial Ecology, where he teaches geo-data and feature analysis, engineering, and processing for geospatial applications.

Research Interests

• Remote Sensing Applications
• Machine Learning for Geospatial Analysis
• Natural Hazard Detection and Monitoring
• Geo-explainable (Geo-X) AI
• Global Early Warning Systems

Selected Publication

Mancino, S., Sblano, A., Lovergine, F. P., Massimi, V., Sethi, T., Capolongo, D., Amatulli, G. – Unified Global Landslide Catalogue (UGLC): A single, standardised global-scale landslide dataset – Earth System Science Data Discussions – 2025
View in Shared Publications