Alessandro Zangari - Researcher page
![Alessandro Zangari's profile picture](assets/me_updated.jpg)
Hello! I am a Ph.D. student in Computer Science at the Ca’ Foscari University of Venice (Italy).
Previously, I obtained
a Master’s Degree in Computer Science at the University of Padua in 2020, with a focus on AI and Machine Learning.
About me
- My name: Alessandro Zangari (unive profile page)
- Affiliation: Ca’ Foscari University of Venice
- Department: Department of Environmental Sciences, Informatics and Statistics
- Supervisor: Prof. Andrea Albarelli
- Contact email: alessandro.zangari@unive.it
Research
My main research interests are Explainable AI (XAI) and Natural Language Processing, but I am also working on XAI methods for Computer Vision tasks. Additionally, I am interested in exploring the ethical implications of machine learning and its effect on society.
My Ph.D. project focuses on developing new scalable and explainable strategies for Machine Learning, with the goal of bridging the gap between the performance of machine learning methods and the intelligibility of their reasoning.
I am also part of the project Interconnected Nord-Est Innovation Ecosystem, where I work on textual data analytics to model tourist behaviour.
Latest publications
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[accepted] Zangari A, Marcuzzo M, Rizzo M, Albarelli A, Gasparetto A. Crossing the Divide: Designing Layers of Explainability. Accepted and to be presented at ICAISC 2024 (June 2024)
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[accepted] Rizzo M, Marcuzzo M, Zangari A, Schiavinato M, Albarelli A, Gasparetto A. Stop overkilling simple tasks with black-box models, use more transparent models instead. Accepted and to be presented at ICPRAI 2024 (July 2024)
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[in review] Rizzo M, Veneri A, Marcuzzo M, Zangari A, Albarelli A, Lucchese C, Nobile M, Conati C. Machine Learning Models Explanations as Interpretations of Evidence: A Theoretical Framework of Explainability and its Implications on High-stakes Biomedical Decision-making. BMC Supplements. In peer review.
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Zangari A, Marcuzzo M, Rizzo M, Giudice L, Albarelli A, Gasparetto A. Hierarchical Text Classification and Its Foundations: A Review of Current Research. Electronics. 2024; 13(7):1199. 10.3390/electronics13071199
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Zangari A, Marcuzzo M, Schiavinato M, Gasparetto A, Albarelli A. Ticket automation: An insight into current research with applications to multi-level classification scenarios. Expert Systems with Applications. 2023;225:119984. 10.1016/j.eswa.2023.119984
For the complete list of papers you can visit my ORCID profile page (link below).