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Ph.D Student in Computer Science and Mathematics
Department of Mathematics, University of Bari Aldo Moro
Short Bio:
Gaetano Settembre is a Ph.D. student in the Department of Mathematics at the University of Bari Aldo Moro. He is an active member of the MIDAS Research Group, where his research focuses on the development of low-rank-based models and methodologies for the analysis of Earth Observation data. His interests lie in matrix and tensor factorization, low-rank approximation, machine learning and remote sensing.
Gaetano earned his Bachelor’s Degree in Computer Science, as well as his Master’s Degree in Data Science from the University of Bari. As part of his Ph.D. studies, Gaetano spent six months as a visiting researcher at National Technical University of Athens in Greece and six months at a corporate research with Planetek Italia S.r.l., gaining valuable international and industry experience.
For complete Gaetano Settembre's web page please refer to: https://gaetanosettembre.github.io
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Submitted Articles:
Superpixel-based plastic litter detection in UAV hyperspectral imaging using spectral-textural features. G. Settembre, G. Gargano, N. Del Buono (2025). Proceedings of Knowledge Based and Intelligent information and Engineering Systems, KES 2025. Procedia Computer Science. [Accepted]
AI in Pediatric Urology: Deep Learning-based Approach supporting Posterior Urethral Valves Diagnosis on VCUG Imaging. C. Russo, G. Settembre, G. Gargano, M.S. de Biase, R. De Fazio (2025). Proceedings of International Conference on Image Analysis and Processing - ICIAP 2025 Workshops. Lecture Notes in Computer Science. [Accepted]
AI-Driven Insights into Microbial Biomarkers for Colorectal Cancer Progression. G. Gargano, G. Settembre, N. Del Buono (2025). Proceedings of Knowledge Based and Intelligent information and Engineering Systems, KES 2025. Procedia Computer Science. [Accepted]
List of recent publications:
Advancing blind hyperspectral unmixing in remote sensing: comparing deep-inspired subspace learning methods. G. Settembre, F. Esposito, N. Del Buono (2025). Advanced Modeling and Simulation in Engineering Sciences, vol XX, pp. XXX-XXX.
A land cover change framework analyzing wildfire-affected areas in bitemporal PRISMA hyperspectral images. G. Settembre, N. Taggio, N. Del Buono, F. Esposito, P. Di Lauro, A. Aiello (2024). Mathematics and Computers in Simulation, vol. 229, pp. 855-866.
Enhanced MRI Brain Tumor Detection and Classification via Topological Data Analysis and Low-Rank Tensor Decomposition. S.G. De Benedictis, G. Gargano, G. Settembre. Journal of Computational Mathematics and Data Science, vol. 13 (2024), p.100103.
Deep NMF and Autoencoder: A Comparative Analysis for Hyperspectral Unmixing Using PRISMA Real Images.
G. Settembre, N. Del Buono, F. Esposito, N. Taggio. IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 3708-3712.Low-rank hierarchical clustering of PRISMA hyperspectral images to identify burned areas. G. Settembre, N. Taggio, N. Del Buono, A. Aiello, F. Esposito. International Workshops of ECML PKDD 2023, Revised Selected Papers, Part III in Communications in Computer and Information Science, vol 2135.
CrystalMELA: a new crystallographic machine learning platform for crystal system determination. N. Corriero, R. Rizzi, G. Settembre, N. Del Buono, and D. Diacono. Journal of Applied Crystallography (IUCr), vol. 56, no. 2, 2023.
Machine Learning approaches for predicting Crystal Systems: a brief review and a case study. G. Settembre, N. Corriero, N. Del Buono, F. Esposito, R. Rizzi. Conference proceedings Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13810, pp. 93-107.
Contacts
E-mail: gaetano.settembre@uniba.it
Address: Room 16, Second floor, Dept. of Mathematics, Via E. Orabona, 4, Bari, Italy
Office Tel: +39 080 5443387
Website: https://gaetanosettembre.github.io
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