BeFair: Addressing Fairness in the Banking Sector. - Alessandro Castelnovo; Riccardo Crupi; Giulia Del Gamba; Greta Greco; Aisha Naseer; Daniele Regoli; Beatriz San Miguel González (IEEE BigData, 2020)

Towards Fairness Through Time. - Alessandro Castelnovo; Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Andrea Cosentini (PKDD/ECML Workshops (1), 2021)

The zoo of Fairness metrics in Machine Learning. - Alessandro Castelnovo; Riccardo Crupi; Greta Greco; Daniele Regoli (CoRR, 2021)

Investigating Bias with a Synthetic Data Generator: Empirical Evidence and Philosophical Interpretation. - Alessandro Castelnovo; Riccardo Crupi; Nicole Inverardi; Daniele Regoli; Andrea Cosentini (BEWARE@AI*IA, 2022)

Leveraging Causal Relations to Provide Counterfactual Explanations and Feasible Recommendations to End Users. - Riccardo Crupi; Beatriz San Miguel González; Alessandro Castelnovo; Daniele Regoli (ICAART (2), 2022)

Extending Decision Tree to Handle Multiple Fairness Criteria. - Alessandro Castelnovo (IJCAI, 2022)

FFTree: A flexible tree to handle multiple fairness criteria. - Alessandro Castelnovo; Andrea Cosentini; Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica (Inf. Process. Manag., 2022)

Marrying LLMs with Domain Expert Validation for Causal Graph Generation (short paper). - Alessandro Castelnovo; Riccardo Crupi; Fabio Mercorio; Mario Mezzanzanica; Daniele Potertì; Daniele Regoli (AIABI@AI*IA, 2023)

Preserving Utility in Fair Top-k Ranking with Intersectional Bias. - Nicola Alimonda; Alessandro Castelnovo; Riccardo Crupi; Fabio Mercorio; Mario Mezzanzanica (BIAS, 2023)

An Open-Source Toolkit to Generate Biased Datasets. - Joachim Baumann 002; Alessandro Castelnovo; Riccardo Crupi; Nicole Inverardi; Daniele Regoli (EWAF, 2023)

Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias. - Joachim Baumann 002; Alessandro Castelnovo; Riccardo Crupi; Nicole Inverardi; Daniele Regoli (FAccT, 2023)

Bias On Demand: Investigating Bias with a Synthetic Data Generator. - Joachim Baumann 002; Alessandro Castelnovo; Andrea Cosentini; Riccardo Crupi; Nicole Inverardi; Daniele Regoli (IJCAI, 2023)

Leveraging Group Contrastive Explanations for Handling Fairness. - Alessandro Castelnovo; Nicole Inverardi; Lorenzo Malandri; Fabio Mercorio; Mario Mezzanzanica; Andrea Seveso (xAI (3), 2023)

Fair Enough? A map of the current limitations of the requirements to have "fair" algorithms. - Alessandro Castelnovo; Nicole Inverardi; Gabriele Nanino; Ilaria Giuseppina Penco; Daniele Regoli (CoRR, 2023)

Fair Enough? A Map of the Current Limitations of the Requirements to Have Fair Algorithms (Short paper). - Daniele Regoli; Alessandro Castelnovo; Nicole Inverardi; Gabriele Nanino; Ilaria Giuseppina Penco (DP@AI*IA, 2024)

Augmenting XAI with LLMs: A Case Study in Banking Marketing Recommendation. - Alessandro Castelnovo; Roberto Depalmas; Fabio Mercorio; Nicolò Mombelli; Daniele Potertì; Antonio Serino; Andrea Seveso; Salvatore Sorrentino; Laura Viola (xAI (1), 2024)

Integrating XAI for Predictive Conflict Analytics. - Luca Macis; Marco Tagliapietra; Alessandro Castelnovo; Daniele Regoli; Greta Greco; Andrea Claudio Cosentini; Paola Pisano; Edoardo Carroccetto (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)

Towards Responsible AI in Banking: Addressing Bias for Fair Decision-Making. - Alessandro Castelnovo (CoRR, 2024)

Counterfactual explanations as interventions in latent space. - Riccardo Crupi; Alessandro Castelnovo; Daniele Regoli; Beatriz San Miguel González (Data Min. Knowl. Discov., 2024)

Evaluative Item-Contrastive Explanations in Rankings. - Alessandro Castelnovo; Riccardo Crupi; Nicolò Mombelli; Gabriele Nanino; Daniele Regoli (Cogn. Comput., 2024)

A Survey on Human Resource Management Under the AI Act: Ethical, Practical, and Regulatory Perspectives. - Nicola Alboré; Alessandro Castelnovo; Matteo Della Valle; Andrea Ermellino; Luca Puggini; Silvia Tessaro (AIMMES, 2025)