How to Deal with Different Densities of Urban Spatial Data? A Comparison of Clustering Approaches to Detect City Hotspots. - Eugenio Cesario; Paolo Lindia; Andrea Vinci (NUMTA (3), 2023)

Detecting Multi-Density Urban Hotspots in a Smart City: Approaches, Challenges and Applications. - Eugenio Cesario; Paolo Lindia; Andrea Vinci (Big Data Cogn. Comput., 2023)

Enhancing the Evaluation of Fault Detection Models in Smart Agriculture Using LLM Agents for Rule-Based Anomaly Generation. - Paolo Lindia; Riccardo Cantini; Francesco Bettucci; Luigi Sartori; Paolo Trunfio (GreenAI@AI*IA, 2024)

Towards a Hierarchical Exascale Framework for Iterative Parallel Data Analysis Algorithms. - Eugenio Cesario; Paolo Lindia (PDP, 2024)

A scalable multi-density clustering approach to detect city hotspots in a smart city. - Eugenio Cesario; Paolo Lindia; Andrea Vinci (Future Gener. Comput. Syst., 2024)

Multi-density crime predictor: an approach to forecast criminal activities in multi-density crime hotspots. - Eugenio Cesario; Paolo Lindia; Andrea Vinci (J. Big Data, 2024)

Improving Cloud Energy Efficiency through Machine Learning Models. - Eugenio Cesario; Paolo Lindia; Federica Lobello; Andrea Vinci; Shabnam Zarin; Santina Capalbo (PDP, 2025)

Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What's the Best Approach for Crime Forecasting? - Eugenio Cesario; Paolo Lindia; Andrea Vinci (IEEE Access, 2025)