Matteo Marcuzzo

About Me

I am a Ph.D. student at in Computer Science at the Ca’ Foscari University of Venice (Italy). Prior to this, I earned a Master’s Degree in Computer Science from the University of Padua (Italy), with a curricula focused on AI and software development. Additionally, I hold a BSc in Computer Games Technology from the University of the West of Scotland (UK).

My primary academic interests revolve around explainable and trustworthy AI, with a focus on Natural Language Processing. Additionally, I’ve delved into explainable AI techniques for Computer Vision tasks, and I am currently exploring the possibilities provided by explanation techniques for graph-based methods.

Beyond academics, I’m passionate about videogame design, music, and animals.

Research Interests

• Explainable AI: Explanation techniques, transparent models, XAI frameworks;
• Natural Language Processing: Text classification, summarization, interpretable NLP models;
• Graph Learning: Graph Neural Networks, explanation techniques for graph-based methods;
• Fuzzy Logic: Data-driven Fuzzy Inference Systems, Fuzzy Neural Networks.

In Review / Due to Be Published

• [July. 2024] Matteo Rizzo, Matteo Marcuzzo, Alessandro Zangari, Michele Schiavinato, Andrea Albarelli, Andrea Gasparetto. Stop overkilling simple tasks with black-box models, use more transparent models instead. Accepted and to be presented at ICPRAI 2024
• [June. 2024] Alessandro Zangari, Matteo Marcuzzo, Matteo Rizzo, Andrea Albarelli, Andrea Gasparetto. Crossing the Divide: Designing Layers of Explainability. Accepted and to be presented at ICAISC 2024.
• [In review] Matteo Rizzo, Alberto Veneri, Matteo Marcuzzo, Alessandro Zangari, Andrea Albarelli, Claudio Lucchese, Marco Nobile, Cristina Conati. Machine Learning Models Explanations as Interpretations of Evidence: A Theoretical Framework of Explainability and its Implications on High-stakes Biomedical Decision-making. BMC Supplements.

Full List of Publications

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