Research

Luca Corbucci, Javier Alejandro Borges Legrottaglie, Francesco Spinnato, Anna Monreale, Riccardo Guidotti - An Interpretable Data-Driven Unsupervised Approach for the Prevention of Forgotten Items. Accepted at at the 28th European Conference on Artificial Intelligence (ECAI 2025) - Bologna, Italy 🇮🇹
Luca Corbucci, Francesca Naretto, Anna Monreale - Enhancing Local Explanations with GAN-Based neighborhood generation - Accepted at Discovery Science'25 - Lubjana, Slovenia 🇸🇮
Xenia Heilmann, Luca Corbucci, Mattia Cerrato, Anna Monreale -FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation
Xenia Heilmann, Luca Corbucci, Mattia Cerrato - A Benchmark for Client-level Fairness in Federated Learning. Accepted at Fourth European Workshop on Algorithmic Fairness (EWAF) 2025 - Eindhoven, The Netherlands 🇳🇱
Luca Corbucci, Xenia Heilmann, Mattia Cerrato - Benefits of the Federation? Analyzing the Impact of Fair Federated Learning at the Client Level. Accepted at ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2025 - Athens, Greece 🇬🇷
Valerio Bonsignori, Luca Corbucci, Francesca Naretto, Anna Monreale - Differentially Private FastSHAP for Federated Learning Model Explainability. Accepted at International Joint Conference on Neural Networks (IJCNN) 2025 - Rome, Italy 🇮🇹

Luca Corbucci, Mikko A Heikkila, David Solans Noguero, Anna Monreale, Nicolas Kourtellis - PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning. Presented at the 27th European Conference on Artificial Intelligence (ECAI 2024) - Santiago de Compostela, Spain 🇪🇸
Luca Corbucci, Anna Monreale, Roberto Pellungrini - Enhancing Privacy and Utility in Federated Learning: A Hybrid P2P and Server-Based Approach with Differential Privacy Protection. Presented at the 21st International Conference on Security and Cryptography (SECRYPT 2024) - Djion, France 🇫🇷

Luca Corbucci, Anna Monreale, Cecilia Panigutti, Michela Natilli, Simona Smiraglio, Dino Pedreschi - Semantic enrichment of explanations of AI models for healthcare - Presented at Discovery Science'23 - Porto, Portugal 🇵🇹
Luca Corbucci, Riccardo Guidotti, Anna Monreale (2023) - Explaining Black-Boxes in Federated Learning - Presented at Xai World Conference 2023 - Lisbon, Portugal 🇵🇹

Luca Corbucci, Anna Monreale, Cecilia Panigutti, Michela Natilli, Simona Smiraglio, Dino Pedreschi (2022) - Semantic Enrichment of XAI Explanation for healthcare - Presented at ICAI'22 - Online

Elia Bisconti, “Towards Personalized Explainability: The development of a Modular Recommender System to Assess Explanation Suitability for Different Personas”, Master Degree in Computer Science, 2025
Javier Alejandro Borges Legrottaglie, “A Data-Driven Unsupervised Approach for the Prevention of Forgotten Items", Master Degree in Digital Humanities, 2025
Francesco Cappellini, “Federated Explainable Artificial Intelligence: A Case Study", One-year Master in Big Data Analytics & Social Mining, 2023

CISPA - ELLIS - Summer School 2025 - 04 August - 08 August, 2025 - Saarbrücken, Germany 🇩🇪
IJCNN 2025 - 30 June - 5 July, 2025- Rome, Italy 🇮🇹
Facct 2025 - 22 June - 26 June, 2025 - Athens, Greece 🇬🇷
ECAI 2024 - 21 October - 24 October, 2024 - Santiago De Compostela, Spain 🇪🇸
Summer School on Security & Privacy in the Age of AI 2024 - 10 September - 13 September, 2024 - Leuven, Belgium 🇧🇪
M2L: Mediterranean Machine Learning Summer School - 28th August - 2nd September, 2023 - Thessaloniki, Greece 🇬🇷
XAI World Conference 2023 - 25th - July 28rd, 2023. Lisbon, Portugal 🇵🇹
Lipari Summer School - DATA SCIENCE: Models, Algorithms, AI and Beyond July - 17th - July 23rd, 2022. Lipari 🇮🇹
HHAI: The first International Conference on Hybrid Human-Artificial Intelligence - 13-17 June 2022, Amsterdam 🇳🇱