Matteo GRAZIOSO
- Qualifica
- Dottorando
- Dottorato
-
INFORMATICA
41° Ciclo - Immatricolati nel 2025
- Area tematica
- Interpretable and Fairness-preserving AI for High-Risk Applications
- Supervisore
- Marco Salvatore Nobile, Daniela Besozzi (Università degli Studi di Milano-Bicocca)
- Sito web
-
https://www.unive.it/web/it/18697/persone/matteo.grazioso(scheda personale)
https://matteograzioso.com/
- Struttura
-
Dipartimento di Scienze Ambientali, Informatica e Statistica
Sito web struttura: https://www.unive.it/dais
Didattica anno corrente
Didattica anni precedenti
Attività e competenze di ricerca
- Computational drug discovery
-
- Altri membri del gruppo di ricerca:
-
Alessandro ANGELINI
Leone BACCIU
Achille GIACOMETTI
Silvia MULTARI
Marco Salvatore NOBILE
- Modeling, simulation and analysis of complex systems in astrophysics
-
- SSD:
- INF/01
- Altri membri del gruppo di ricerca:
-
Leone BACCIU
Marco Salvatore NOBILE
Sabina ROSSI
Pubblicazioni in evidenza
Della Torre, Stefano; Bacciu, Leone; Grazioso, Matteo; Cavallotto, Giovanni; Gervasi, Massimo; La Vacca, Giuseppe; Rossi, Sabina; Nobile, Marco S. Validation of COSMICA code for massive stochastic simulation of cosmic rays propagation in the heliosphere in ASTRONOMY AND COMPUTING, vol. 55 (ISSN 2213-1337)
DOI 2026,
Articolo su rivista - Scheda ARCA: 10278/5112968
Papetti, Daniele M.; Nobile, Marco S.; Grazioso, Matteo; Cazzaniga, Paolo; Vanneschi, Leonardo; Besozzi, Daniela HyCAPS: A Settings-Free Optimization Heuristics Integrating Evolutionary Computation and Swarm Intelligence , International Conference on the Applications of Evolutionary Computation (Part of EvoStar) 2026, Springer, pp. 375-390, Convegno: EvoApplications 2026 (ISBN 9783032236067; 9783032236074) (ISSN 0302-9743)
DOI 2026,
Articolo in Atti di convegno - Scheda ARCA: 10278/5116368
Bacciu, Leone; Grazioso, Matteo; Cavallotto, Giovanni; Della Torre, Stefano; Gervasi, Massimo; La Vacca, Giuseppe; Rossi, Sabina; Nobile, Marco S. Massive stochastic simulation of cosmic rays propagation in the heliosphere: The COSMICA code in ASTRONOMY AND COMPUTING, vol. 55 (ISSN 2213-1337)
DOI 2025,
Articolo su rivista - Scheda ARCA: 10278/5107828
Grazioso, Matteo; Gallese, Chiara; Vanneschi, Leonardo; Nobile, Marco S. A Survey of Modern Hybrid Particle Swarm Optimization Algorithms , International Conference on the Applications of Evolutionary Computation (Part of EvoStar), Pablo García-Sánchez, Emma Hart, Sarah L. Thomson, pp. 107-128, Convegno: EvoApplications 2025 (ISBN 9783031900648; 9783031900655) (ISSN 0302-9743)
DOI 2025,
Articolo in Atti di convegno - Scheda ARCA: 10278/5093927
Nobile, Marco S.; Lupi, Amalia; Bacciu, Leone; Grazioso, Matteo; Gallese, Chiara; Quaia, Emilio; Pepe, Alessia Assessing Cardiac Functionality by Means of Interpretable AI and Myocardial Strain , 2025 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), IEEE, pp. 1-9, Convegno: 2025 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 20-22 August 2025
DOI 2025,
Articolo in Atti di convegno - Scheda ARCA: 10278/5104048
Tutte le pubblicazioni
Curriculum vitae
Matteo Grazioso is a Ph.D. Student in Computer Science at Ca’ Foscari University of Venice (Department of Environmental Sciences, Informatics and Statistics).
His primary research focuses on Interpretable and Fairness-preserving AI for High-Risk applications, where he explores the design of trustworthy AI systems, ensuring that Machine Learning models in high-stakes domains are both transparent and ethically aligned.
Matteo’s research interests lie at the intersection of Computational Intelligence, Machine Learning, Interpretable AI, High-Performance Computing, Evolutionary Drug Discovery, and Optimization Algorithms. He holds a Master’s Degree in Computer Science – Artificial Intelligence and Data Engineering –, graduated summa cum laude from Ca’ Foscari University of Venice, where he also served as a Research Grant Holder.
In parallel with his doctoral studies, Matteo serves as a Scientific Associate at the Italian National Institute of Nuclear Physics (INFN), Milano Bicocca Division, and is a Visiting Ph.D. Student at the University of Milano-Bicocca (Department of Informatics, Systems and Communication).
He is an active member of the FRACTALS Research Group (Fair and Responsible Algorithms for Complex-systems, Therapeutics, Astrophysics and Life-Sciences), where he contributes to interdisciplinary research on trustworthy AI, computational intelligence, and high-risk applications.
He is an active member of the IEEE and the IEEE Computational Intelligence Society (CIS). Within the IEEE CIS, he contributes to the Advanced Representation in Biological and Medical Search and Optimization (ARBM) Task Force under the Bioinformatics & Bioengineering Technical Committee (BBTC), and the AI Governance, Regulation and Compliance (AIRC) Task Force under the Ethical, Legal, Social, Environmental and Human Dimensions of AI/CI Technical Committee (SHIELD).
For further information, please visit his personal website at matteograzioso.com or connect via LinkedIn.
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