报告人：Filippo Catani（意大利帕多瓦大学 教授）

时间：2024年10月22日（周二）10:00-11:30

地点：空间信息中心204会议室

报告简介：

Artificial intelligence (AI) offers advanced capabilities and analysis tools to landslide risk assessment. Various machine learning and deep learning algorithms helps in the identification and prediction of temporal and spatial landslide risk patterns, leading to more effective geological risk mitigation strategies and landslide early warning systems.

This seminar will cover previous works of AI theory and application in landslide risk assessment including landslide mapping, landslide susceptibility analysis, landslide displacement prediction, etc. conducted by Professor Filippo Catani’s research group in University of Padova, eventually focusing on future possible applications of cutting edge AI algorithms in new fields of landslide hazard risk related researches.

报告人简介：

Filippo Catani is Full Professor of Engineering Geology with the Department of Geosciences of the University of Padova and UNESCO Chair Associate on Prevention and Sustainable Management of Geo-Hydrological Hazards with the University of Florence (Italy). He is also member of NASA-JPL informal group on Earth Surface Changes. He received a post graduate degree in Computer Sciences in Polytechnic University of Milan and a PhD in Engineering Geology in University of Padova and Ferrara. In 1996, he has been visiting PhD student at the University of Berkeley (California). From 1998 to 1999 he has been visiting scientist at the Massachusetts Institute of Technology to work with the Parson’s Lab Hydrology Group. He is advisor and reviewer for EC H2020 and Future Europe 2030 research projects. He is editor of the journal “Natural Hazards and Earth System Sciences (EGU)”, “Geoenvironmental Disasters (Springer)” and guest editor of the journal “Landslides (Springer)” and “Remote Sensing (MDPI)”. He has been guest editor of special issues for several other journals. He is author of more than 100 papers in international journals. His research interests mainly include engineering geology, landslide hazard and risk analysis, remote sensing of Earth surface processes and landforms, landscape analysis, geomorphometry.