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Marco Fiorucci

Marie Skłodowska-Curie Fellow
Cultural Heritage Technologies
Research center

Marco Fiorucci is an Experienced Researcher Marie Curie in Machine Learning at the Centre for Cultural Heritage Technology (CCHT) of the Istituto Italiano di Tecnologia (IIT). He is working mainly in the fields of Machine Learning, with particular emphasis on optimal transport. In this context, Marco has won a MSCA-IF for his OPTIMAL project that aims to develop an efficient and principled Machine Learning  approach based on Optimal Transport to automatically detect looting (past and present) directly on airborne  LiDAR point cloud time-series. He is a computer scientist with a solid broad background, spanning from Physics and Machine Learning to Graph Theory and Statistics, who has successfully worked on several different interdisciplinary projects both in academia and in industry. He received the Master degree (summa cum laude) and his PhD in Computer Science from Ca’ Foscari University of Venice respectively in 2015 and 2019. He held visiting research position at the University of Alicante and at VTT (Finland). More recently, he has shifted his attention to the analysis of EO data (multispectral and hyperspectral data) and airborne LiDAR for the detection of sub-surface archaeological sites (ESA-CLS). In addition to research, Marco is one of the co-founder and co-organizer of DataBeersVenezia and one of the communication managers of the CCHT.

All Publications
Fiorucci M., Verschoof-van der Vaart W.B., Soleni P., Le Saux B., Traviglia A.
Deep Learning for Archaeological Object Detection on LiDAR: New Evaluation Measures and Insights
Remote Sensing, vol. 14, (no. 7), pp. 1694
Article Journal
Davoudi H., Fiorucci M., Traviglia A.
Ancient Document Layout Analysis: Autoencoders meet Sparse Coding
25th International Conference on Pattern Recognition
Conference Paper Conference
Fiorucci M., Khoroshiltseva M., Pontil M., Traviglia A., Del Bue A., James S.
Machine Learning for Cultural Heritage: A Survey
Pattern Recognition Letters, vol. 133, pp. 102-108
Article Journal
Fiorucci M., Davoudi H., Traviglia A.
Semi-supervised classification of ancient coins using graph neural networks
Conference on Computer Applications and Quantitative Methods in Archaeology (CAA)
Abstract Report Conference
Fiorucci M., Pelosin F., Pelillo M.
Separating Structure from Noise in Large Graphs Using the Regularity Lemma
Pattern Recognition, vol. 98
Fiorucci M.
L'intelligenza artificiale a servizio dell'arte
Databeers Venezia
Public Event
Scientific Talks
Fiorucci M.
Graph Summarization Using Regular Partition and Its Use in Graph Search
Department of Mathematics and Systems Analysis, Aalto University
Fiorucci M.
Structural Big Data and Regular Partitions
Department of Computer Science and Artificial Intelligence, University of Alicante
Oral presentations
Traviglia A., Fiorucci M.
Graph Convolutional Neural Networks for Cultural Heritage: Applications in RS recognition, numismatics and epigraphy
Machine Learning in Archaeology, Rome
Pelosin F., Fiorucci M., and Pelillo M.
Graph Summarization Using Regular Partitions
The 8th International Conference on Network Analysis, Moscow
Traviglia A., Artesani A., Fiorucci M., Ljubenovic M.
European Physical Journal Plus