This section hosts scientific production, administrative reports, communication materials. The updating of the section reflects the progress of the project and the status of the research. 



Journal papers:

  1. Gonzalez-Diaz, R., Manuel Soriano-Trigueros, and A. Torras-Casas. "Partial matchings induced by morphisms between persistence modules." Computational Geometry 112 (2023): 101985.
  2. Narteni, Sara, Marco Muselli, Fabrizio Dabbene, and Maurizio Mongelli. "Trustworthy artificial intelligence classification-based equivalent bandwidth control." Computer Communications 209 (2023): 260-272.
  3. Ali, Dashti, Aras Asaad, Maria-Jose Jimenez, Vidit Nanda, Eduardo Paluzo-Hidalgo, and Manuel Soriano-Trigueros. "A survey of vectorization methods in topological data analysis." IEEE Transactions on Pattern Analysis and Machine Intelligence (2023).
  4. Carlevaro, Alberto, Marta Lenatti, Alessia Paglialonga, and Maurizio Mongelli. "Multi-Class Counterfactual Explanations using Support Vector Data Description." IEEE Transactions on Artificial Intelligence (2023).

Conference papers:

  1. Cairoli, Francesca, Nicola Paoletti, and Luca Bortolussi. "Conformal quantitative predictive monitoring of STL requirements for stochastic processes." In Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control, pp. 1-11. 2023.
  2. Corradini, Franca, Francesco Flammini, and Alessandro Antonucci. "Probabilistic Modelling for Trustworthy Artificial Intelligence in Drone-Supported Autonomous Wheelchairs." In Proceedings of the First International Symposium on Trustworthy Autonomous Systems, pp. 1-5. 2023.
  3. Carlevaro, Alberto, Giacomo De Bernardi, Marta Lenatti, Sara Narteni, Marco Muselli, Alessia Paglialonga, Fabrizio Dabbene, and Maurizio Mongelli. "ARE DIGITAL TWINS SUITABLE TO DRIVE SAFE AI?."
  4. De Bernardi, Giacomo, Sara Narteni, Enrico Cambiaso, Marco Muselli, and Maurizio Mongelli. "Weighted Mutual Information for Out-Of-Distribution Detection." In World Conference on Explainable Artificial Intelligence, pp. 318-331. Cham: Springer Nature Switzerland, 2023.
  5. Cairoli, Francesca, Luca Bortolussi, and Nicola Paoletti. "Learning-based approaches to predictive monitoring with conformal statistical guarantees." In International Conference on Runtime Verification, pp. 461-487. Cham: Springer Nature Switzerland, 2023.
  6. Ben Batten, Mehran Hosseini and Alessio Lomuscio. “Tight Verification of Probabilistic Robustness in Bayesian Neural Networks.” Accepted at the Artificial Intelligence and Statistics (AISTATS) 2024 conference.


  1. Carlevaro, Alberto, Sara Narteni, Fabrizio Dabbene, Marco Muselli, and Maurizio Mongelli. "CONFIDERAI: a novel CONFormal Interpretable-by-Design score function forExplainable and Reliable Artificial Intelligence." arXiv preprint arXiv:2309.01778 (2023).
  2. Paluzo-Hidalgo, Eduardo, Miguel A. Gutiérrez-Naranjo, and Rocio Gonzalez-Diaz. "Explainability in Simplicial Map Neural Networks." arXiv preprint arXiv:2306.00010 (2023).
  3. Torras-Casas, Álvaro, Eduardo Paluzo-Hidalgo, and Rocio Gonzalez-Diaz. "A Topological Approach to Measuring Training Data Quality." arXiv preprint arXiv:2306.02411 (2023).
  4. De Bernardi, Giacomo, Sara Narteni, Enrico Cambiaso, and Maurizio Mongelli. "Rule-based out-of-distribution detection." arXiv preprint arXiv:2303.01860 (2023).
  5. Gonzalez-Diaz, Rocio, Manuel Soriano-Trigueros, and Álvaro Torras-Casas. "Additive Partial Matchings Induced by Persistence Morphisms." arXiv preprint arXiv:2006.11100 (2020).