Gaetano Settembre

I'm

TMC Italia SpA Employeneur at Leonardo SpA - Space Division
University of Bari Aldo Moro

About me

I am an AI/ML Researcher & Engineer at Leonardo S.p.A. - Space Division, employed by TMC Italia S.p.A.. My work focuses on the development and implementation of AI/ML-based on-board processing solutions for innovative satellite payloads, designing intelligent near real-time data pipelines that (i) minimise downlink requirements, (ii) reduce ground processing dependencies, and (iii) enable rapid alerting for environmental monitoring and surveillance scenarios.
In parallel, I am completing my Ph.D. in Computer Science and Mathematics at the University of Bari Aldo Moro, where I have been conducting research activities since October 2022 through a scholarship co-funded by the University of Bari and Planetek Italia S.r.l..
I received my Master's Degree in Data Science (LM-91) from the University of Bari Aldo Moro in 2022 with honorable mention for academic excellence, completing a thesis on "Analysis of crystallographic data and training of supervised predictive models". Prior to this, I obtained my Bachelor's Degree in Computer Science (L-31) from the same university in 2019.
My doctoral research is supervised by Prof. Nicoletta Del Buono (academic supervisor and team leader of Mathematics In Data AnalysiS (MIDAS) Research Group), Eng. Cristoforo Abbattista, and Dr. Nicolò Taggio (industrial supervisors). As part of my Ph.D. studies, I spent a research period as a visiting researcher at the Remote Sensing Laboratory of the National Technical University of Athens, working within the research group led by Prof. Vassilia Karathanassi.
I maintain active memberships in several organizations, including IEEE, the IEEE Geoscience and Remote Sensing Society (GRSS), Postgraduate Researchers in Inverse Problems, Machine Learning and Optimization (PRIMO), the Italian Society of Applied and Industrial Mathematics (SIMAI), INdAM-GNCS, and the KES Intelligent Systems Society.

News 🎉

[Jan '26] Our research article AI in Pediatric Urology: Deep Learning-Based Approach Supporting Posterior Urethral Valves Diagnosis on VCUG Imaging was published in proceedings of ICIAP 2025.
[Dec '25] I started a new position as an AI/ML Researcher & Engineer at Leonardo S.p.A. - Space Division, employed by TMC Italia S.p.A..
[Oct '25] Our research article Advancing blind hyperspectral unmixing in remote sensing: comparing deep-inspired subspace learning methods was published in Advanced Modeling and Simulation in Engineering Sciences.
[Oct '25] I am selected to attend the Winter School GAIA 2025 - Generative AI and Actions for a changing world in Rimini (17-20 November 2025).
[Apr '25] Our Workshop proposal on Innovative Medical image Processing with AI-driven preCision Technologies (IMPACT) has been accepted in 23rd International Conference on Image Analysis and Processing (ICIAP 2025), Rome, Italy
[Apr '25] Our Minisymposium proposal on Advanced Numerical Methods and Machine Learning Techniques in Applied Science has been accepted at Biennial congress of the Italian Society of Applied and Industrial Mathematics (SIMAI 2025), Trieste, Italy
[Mar '25] Our Invited Session proposal on Smart Observation And Preservation for Earth (SOAP4Earth) has been accepted in 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025), Osaka, Japan.
[Feb '25] Our GNCS project MODA: Integrating MOdel-based and DAta-Driven Methods for Multiscale Biological Systems has been approved and funded with a total grant of €1,500.
[Jan '25] Our conference paper Low-Rank Hierarchical Clustering of PRISMA Hyperspectral Images to Identify Burned Areas was published in Proceeding of Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2023.
[Nov '24] I attended the Masterclass: Tensor Decompositions and Applications in Multi-Omics Data Analysis held by Neriman Tokcan (U. Massachussets, Boston, US).
[Nov '24] Our research article A land cover change framework analyzing wildfire-affected areas in bitemporal PRISMA hyperspectral images was published in Mathematics and Computers in Simulation.
[Oct '24] Our research article Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decomposition was published in Journal of Computational Mathematics and Data Science.
[Oct '24] I am on the Local Staff of the 3rd Workshop of UMI Group Mathematics for Artificial Intelligence and Machine Learning, 29-31 January, 2025, University of Bari Aldo Moro.
[Aug '24] I am on the Program and Technical committee of the second Invited Session on Leveraging Digital Twins in Healthcare (LDTH) in conjunction with the 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025), Japan.
[Jul '24] I attended the 2024 IEEE International Geoscience And Remote Sensing Symposium, July 07-14, 2024, Athens, Greece.

Professional Experience

AI/ML Researcher & Engineer - Engineering Consultant

Dec 2025 - Present

TMC Italia S.p.A. (at Leonardo S.p.A. - Space Division), IT

Design and development of AI/ML algorithms for on-board processing of spaceborne sensors
Implementation of lightweight and deployable models for Earth Observation and satellite data analysis
Collaboration with multidisciplinary teams (system engineers, payload experts, data scientists) to integrate AI solutions in operational workflows
Technology transfer from academic research to industrial applications

Education

Ph.D. in Computer Science and Mathematics

Oct 2022 - Oct 2025

University of Bari Aldo Moro, IT

Scholarship D.M. 352/22 in agreement with the company Planetek Italia S.r.l., for Curriculum 2 Mathematics (ex. MAT/08, now MATH-05/A), with theme bound by title: "Low-rank models for the analysis of Earth Observation data focusing on coastal and marine environments". The research project focuses on studying and developing low rank approximation (LRA) computational models able to integrate heterogeneous data, hyper/multispectral images, and sensor data, to better understand the environmental phenomena these data represent. Existing LRA methods are tools for the representation and analysis of multivariate large datasets used in various application areas. The project aims to construct variants of LRA using constrained optimization algorithms based on appropriate cost functions. These will allow adding ad- hoc constraints on the latent components to be extracted from Earth observation data, marine and coastal data, to improve the quality of the resulting approximation model.

M.Sc. degree (Hons.) in Data Science

Sep 2019 - Mar 2022

University of Bari Aldo Moro, IT

Data Mining, Machine Learning, Mathematics and programming for Data Science, Management of structured and unstructured data, Processing of sensitive data, Statistical modeling, Numerical methods for Data Science, Management and analysis of Big Data, Decision-making and optimization models, data-driven economic models, Sentiment Analysis, Recommender Systems.

Curricular Internship activities at Institute of Crystallography c/o CNR:

ETL (Extract, Transform, Load) process of crystallographic data from open source databases
Exploratory analysis of crystallographic data and non-parametric statistical tests
Training, evaluation and tuning of Machine Learning models for crystal system determination (multi-class classification task)
High-performance Models Deployment and development of Web Platform called CrystalMELA (Crystallography MachinE LeArning)

Thesis: "Analysis of crystallographic data and training of supervised predictive models" [Link to CrystalMELA here]
Supervisors: Prof. Nicoletta Del Buono, Dr. Nicola Corriero, Dr. Rosanna Rizzi

B.Sc. in Computer Science

Sept 2015 - Apr 2019

University of Bari Aldo Moro, IT

Problem solving and software development, Discrete mathematics, Computer architecture, Operating systems, English for IT, Programming laboratory; Algorithms and data structures, Databases, Statistics, Software engineering, Advanced programming methods, Mathematical analysis, Numerical calculation; Computer networks, Knowledge engineering, Usability and UX, Information Retrieval.

Curricular Internship activities at SER&Practices (SER&P):

Development of 'Serious games' following the RedTeam vs. Blue Team approach to improve the skills of the SOC (Security Operation Center) and CSRIT (Computer Security Incident Response Team) team
Study of malicious attack scenarios on Linux Servers and Web Applications with the intention of extracting sensitive data using the Cyber Kill Chain framework
Penetration Test and Vulnerability Assessment
Data collection, data analysis (logs, alerts, etc.) and reporting using the IBM Security QRadar SIEM

Thesis: "Red Team vs Blue Team: Data Exfiltration in Government"
Supervisor: Prof. Danilo Caivano

Publications

In this section, you'll find a list of my publications. I always try to provide a freely accessible version of all of my papers, to ensure that everyone can read them. Depending on the publisher, though, the ways I can do that may vary.

Published Articles

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
Proceedings of Image Analysis and Processing - ICIAP 2025 Workshops. Lecture Notes in Computer Science, vol 16170, pp. 138-149.
Superpixel-based plastic litter detection in UAV hyperspectral imaging using spectral-textural features
G. Settembre, G. Gargano, N. Del Buono
Proceedings of Knowledge Based and Intelligent information and Engineering Systems, KES 2025. Procedia Computer Science, vol. 270, pp. 4997-5006.
AI-Driven Insights into Microbial Biomarkers for Colorectal Cancer Progression
G. Gargano, G. Settembre, N. Del Buono
Proceedings of Knowledge Based and Intelligent information and Engineering Systems, KES 2025. Procedia Computer Science, vol. 270, pp. 4936-4945
Advancing blind hyperspectral unmixing in remote sensing: comparing deep-inspired subspace learning methods
G. Settembre, F. Esposito, N. Del Buono
Advanced Modeling and Simulation in Engineering Sciences. vol. 12 (30).
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
Mathematics and Computers in Simulation, vol. 229 (2024), 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, 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
Proceedings Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2023. Communications in Computer and Information Science, vol 2135. pp. 412-423
CrystalMELA: a new crystallographic machine learning platform for crystal system determination
N. Corriero, R. Rizzi, G. Settembre, N. Del Buono, D. Diacono
Journal of Applied Crystallography vol. 56, pt. 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
Proceedings Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13810. pp. 93-107, Springer, Cham

Activities

Here, you'll find a collection of contributions that reflect my involvement in knowledge dissemination, student mentorship, project participation, and other activities related to academic career.

Oral/Poster Presentations

"Superpixel-based plastic litter detection in UAV hyperspectral imaging using spectral-textural features"
KES 2025 - Int. Conference on Knowledge Based and Intelligent information and Engineering Systems, 02 Sep 2025, Osaka, JP

"Spatial Informed Hierarchical Clustering for Hyperspectral Imagery via Total Variation" [POSTER]
Math4AIML - Workshop on Mathematics for Artificial Intelligence and Machine Learning, Bari, IT

"Deep NMF and Autoencoder: A Comparative Analysis for Hyperspectral Unmixing Using PRISMA Real Images" [POSTER]
IGARSS 2024 - IEEE International Geoscience and Remote Sensing Symposium, Athens, GR

"Low-rank models for the analysis of Earth Observation data"
PhD Days 2024, 11 Jul 2024, Bari, IT

"Unlocking insights from the sky: Low-rank methods in Remote Sensing"
XMaths Workshop 2023, 21 Dec 2023, Bari, IT

"Low-rank Hierarchical Clustering of PRISMA hyperspectral images to identify burned areas"
MACLEAN: Workshop on Machine Learning for Earth Observation @ECML/PKDD, 18 Sep 2023, Turin, IT

"Low-rank models for the analysis of Earth Observation data"
PhD Days 2023, 11 Jul 2023, Bari, IT

"A low-rank based approximation framework for real world data integration"
Numerical Analysis and Scientific Computation with Applications (NASCA), 06 Jul 2023, Athens, GR

Organizing/Technical Program Committee

Organizer/Chair:

NUMERA: advanced NUmerical MEthods for Real-world Applications, National Workshop - Bari (Italy), Jun 15, 2026 [link]
IMPACT: Innovative Medical image Processing with AI-driven preCision Technologies, Workshop @ICIAP 2025 - Rome (Italy), Sep 15-16, 2025 [link]
Smart Observation And Preservation for Earth (SOAP4Earth), Invited Session @KES 2025 - Osaka (Japan), Sep 10-12, 2025 [link]
Advanced Numerical Methods and Machine Learning Techniques in Applied Science, Minisymposium @SIMAI 2025 - Trieste (Italy), Sep 1-5, 2025 [link]
3rd Workshop of UMI Group Mathematics for AI and Machine Learning, Jan 29-31, 2025 [link]
3rd PRIMO Workshop 2023 - Bari (Italy), Sep 20-22, 2023 [link]
10th XMaths Workshop 2022 - Bari (Italy), Dec 21-22, 2022 [link]

Technical Program Committee (TPC):

Applications and Systems for Healthcare @ACM/SIGAPP Symposium On Applied Computing (SAC 2026) - Thessaloniki (Greece), Mar 23-27, 2026 [link]
2nd Invited Session on Leveraging Digital Twins in Healthcare (LDTH) @KES 2025 - Osaka (Japan), Sep 10-12, 2025 [link]
Invited Session on Leveraging Digital Twins in Healthcare (LDTH) @KES 2024 - Seville (Spain), Sep 11-13, 2024 [link]

Journal/Conference reviewing

Environmental Monitoring and Assessment (ISSN: 1573-2959)
Journal of Systems and Software (ISSN: 1873-1228)
Biomedical Signal Processing and Control (ISSN: 1746-8108)
Nature Scientific Reports (ISSN: 2045-2322)
Forum Geografi (ISSN: 0852-0682)
Journal of Computational Mathematics and Data Science (ISSN: 2772-4158)
Discover Applied Sciences, formerly "SN Applied Sciences" (ISSN: 3004-9261)
WSEAS Transactions on Business and Economics (ISSN: 1109-9526)

ACM/SIGAPP Symposium On Applied Computing (SAC 2026)
International Conference on Image Analysis and Processing (ICIAP 2025)
IEEE International Conference on Neural Networks (IJCNN 2025)
International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2024, 2025)
International Academic Conference on Optics and Photonics (IACOP 2024)

Projects

Marine Biomass Innovation (MBI) project [link]
MODA: Integrating MOdel-based and DAta-Driven Methods for Multiscale Biological Systems (GNCS funded). CUP: E53C24001950001
Low-rank models and Optimization algorithms for Data Analysis (GNCS funded). CUP: E53C23001670001

Tutoring and/or teaching

“Metodi Decisionali e Ottimizzazione”, Degree Course: LM-91 Data Science, exam assistant
“Metodi numerici per la Data Science”. Degree Course: L-35 in Mathematics, exam assistant
“Metodi di Ottimizzazione per la Data Science e l'Intelligenza Artificiale”. Degree Course: LM-40 Mathematics, exam assistant

Others

SHARPER - European Research Night 2025 (Notte Europea dei Ricercatori) - Bari (IT), September 26, 2025
European Research Night 2024 (Notte Europea dei Ricercatori) - Athens (GR), September 27, 2024
European Research Night 2023 (Notte Europea dei Ricercatori) - Bari (IT), September 29, 2023
Volunteer: DeepLearn23 Spring - Bari (IT), April 03-07, 2023 [link]