| 2025 | IJCNN | HEXA: Heterogeneity-aware Exact Aggregation for Efficient Fine-Tuning in Federated Learning. | Marco Garofalo, Massimo Villari, Fakhri Karray |
| 2025 | UCC | Simplifying Federated Learning Deployment: Design and Implementation of the FLeeT Framework. | Pierluigi Dell'Acqua, Marco Garofalo, Francesco la Rosa, Massimo Villari |
| 2024 | ISCC | Flower Full-Compliant Implementation of Federated Learning with Homomorphic Encryption. | Alessio Catalfamo, Lorenzo Carnevale, Marco Garofalo, Massimo Villari |
| 2024 | ISCC | Web-Centric Federated Learning over the Cloud-Edge Continuum Leveraging ONNX and WASM. | Marco Garofalo, Mario Colosi, Alessio Catalfamo, Massimo Villari |
| 2024 | UCC | Enabling Flower for Federated Learning in Web Browsers in the Cloud-Edge-Client Continuum. | Mario Colosi, Alessio Catalfamo, Marco Garofalo, Massimo Villari |
| 2023 | CLOSER | Empirical Analysis of Federated Learning Algorithms: A Federated Research Infrastructure Use Case. | Harshit Gupta, Abhishek Verma, O. P. Vyas, Marco Garofalo, Giuseppe Tricomi, Francesco Longo, Giovanni Merlino, Antonio Puliafito |
| 2023 | UCC | Workflow Engines in the Compute Continuum: a Comparative Analysis. | Marco Garofalo, Gabriele Morabito, Maria Fazio, Antonio Celesti, Massimo Villari |