Marco Fiorucci

Marco Fiorucci is a Researcher in Machine Learning at the Centre for Cultural Heritage Technology (CCHT) at the Istituto Italiano di Tecnologia. His research interests encompass machine learning and computer vision, with a strong emphasis on optimal transport and implicit neural learning, particularly as these methodologies apply to remote sensing data. He was awarded an MSCA-IF for his OPTIMAL project, which aims to develop an efficient machine learning approach based on optimal transport to automatically detect looting (both past and present) from airborne LiDAR point cloud time series. He holds a PhD in Computer Science from Ca’ Foscari University of Venice (2019) and possesses a rich interdisciplinary background that spans computer science, physics, and machine learning. His academic journey includes visiting research positions at Kyoto University (Japan), the University of Alicante (Spain), and the VTT Technical Research Centre of Finland.