Event Recognition Strategies applied in the Mercurio Project. - Davide Azzalini; Fabio Azzalini; Davide Greco; Mirjana Mazuran; Letizia Tanca (MIDAS@PKDD/ECML, 2017)

Ethics-aware Data Governance (Vision Paper). - Letizia Tanca; Paolo Atzeni; Davide Azzalini; Ilaria Bartolini; Luca Cabibbo; Luca Calderoni; Paolo Ciaccia; Valter Crescenzi; Juan Carlos De Martin; Selina Fenoglietto; Donatella Firmani; Sergio Greco; et al. (SEBD, 2018)

Evolution of Financial Time Series Clusters. - Davide Azzalini; Fabio Azzalini; Mirjana Mazuran; Letizia Tanca (SEBD, 2019)

Tracking the Evolution of Financial Time Series Clusters. - Davide Azzalini; Fabio Azzalini; Mirjana Mazuran; Letizia Tanca (DSMM@SIGMOD, 2019)

Modeling and Comparing Robot Behaviors for Anomaly Detection. - Davide Azzalini (AAMAS, 2020)

HMMs for Anomaly Detection in Autonomous Robots. - Davide Azzalini; Alberto Castellini; Matteo Luperto; Alessandro Farinelli; Francesco Amigoni (AAMAS, 2020)

A Minimally Supervised Approach Based on Variational Autoencoders for Anomaly Detection in Autonomous Robots. - Davide Azzalini; Luca Bonali; Francesco Amigoni (IEEE Robotics Autom. Lett., 2021)

MAPF and MAPD: Recent Developments and Future Directions (short paper). - Francesco Amigoni; Davide Azzalini; Nicola Basilico; Benedetta Flammini (AIRO@AI*IA, 2022)

FARGO: A Fair, Context-AwaRe, Group RecOmmender System. - Davide Azzalini; Elisa Quintarelli; Emanuele Rabosio; Letizia Tanca (BIAS, 2022)

SoCRATe: A Recommendation System with Limited-Availability Items. - Davide Azzalini; Fabio Azzalini; Chiara Criscuolo; Tommaso Dolci; Davide Martinenghi; Sihem Amer-Yahia (CIKM, 2022)

SoCRATe: a Framework for Compensating Users Over Time with Limited Availability Recommendations. - Davide Azzalini; Fabio Azzalini; Chiara Criscuolo; Tommaso Dolci; Davide Martinenghi; Letizia Tanca; Sihem Amer-Yahia (SEBD, 2022)

Accounting for Bossy Users in Context-Aware Group Recommendations. - Davide Azzalini; Elisa Quintarelli; Emanuele Rabosio; Letizia Tanca (SEBD, 2022)

Detecting anomalies in the behavior of autonomous robots. - Davide Azzalini (2022)

Multi-Agent Pickup and Delivery in a Dynamic Environment (short paper). - Benedetta Flammini; Davide Azzalini; Francesco Amigoni (AIRO@AI*IA, 2023)

Multi-Agent Pickup and Delivery in Presence of Another Team of Robots. - Benedetta Flammini; Davide Azzalini; Francesco Amigoni (AAMAS, 2023)

Improving Remaining Useful Life Estimation of Lithium-Ion Batteries when Nearing End of Life. - Luca Martiri; Davide Azzalini; Benedetta Flammini; Loredana Cristaldi; Francesco Amigoni (MetroXRAINE, 2023)

Adversarial Data Augmentation for HMM-Based Anomaly Detection. - Alberto Castellini; Francesco Masillo; Davide Azzalini; Francesco Amigoni; Alessandro Farinelli (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

A Distributed Approach for Fault Detection in Swarms of Robots. - Alessandro Carminati; Davide Azzalini; Simone Vantini; Francesco Amigoni (AAMAS, 2024)

Preventing Deadlocks for Multi-Agent Pickup and Delivery in Dynamic Environments. - Benedetta Flammini; Davide Azzalini; Francesco Amigoni (AAMAS, 2024)

Loss Compensation in Multi-Session Recommendation Under Limited Availability. - Davide Azzalini; Fabio Azzalini; Chiara Criscuolo; Tommaso Dolci; Davide Martinenghi; Sihem Amer-Yahia (EDBT, 2024)

A Transfer Learning Approach for Remaining Useful Life Estimation of Lithium-Ion Batteries. - Luca Martiri; Davide Azzalini; Loredana Cristaldi; Francesco Amigoni (MetroInd4.0 & IoT, 2024)

Domain Adversarial Neural Networks for Remaining Useful Life Estimation of Lithium-Ion Batteries. - Luca Martiri; Giuseppe Meli; Luca Pasquarelli; Davide Azzalini; Loredana Cristaldi; Francesco Amigoni (MetroXRAINE, 2024)

Multi-Agent Pickup and Delivery with external agents. - Luca Bonalumi; Benedetta Flammini; Davide Azzalini; Francesco Amigoni (Robotics Auton. Syst., 2025)