Dottorando in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 37o ciclo (2021-2024)
Dipartimento di Elettronica e Telecomunicazioni (DET)
Profilo
Dottorato di ricerca
Argomento di ricerca
Distributed Machine Learning
Tutori
Interessi di ricerca
Biografia
He obtained his Bachelor’s Degree at Politecnico di Torino in Electronic Engineering in 2018. Then, in his Masters’ studies, he joined a double degree program, which allowed him to graduate in ICT For Smart Societies, at Politecnico di Torino, and in Data Science and Engineering, at EURECOM (Biot, France).
From May 2021 he is a PhD student in Electrical, Electronics and Communications Engineering under the supervision of Professor Carla Fabiana Chiasserini. The focus of his research is distributed Machine Learning. In particular, he studies methods such as Federated Learning and Split Learning, in order to find efficient techniques that would allow reducing the energy required to train the increasingly power-demanding Deep Learning models. Also, he is interested in the potential application of diffusion models, a powerful family of generative models, in communication systems for image transmission, in order to decrease bandwidth usage and communication costs.
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- DI GIACOMO, Giuseppe; Malandrino, Francesco; Chiasserini, Carla Fabiana (2024)
Generosity Pays Off: A Game-Theoretic Study of Cooperation in Decentralized Learning. In: IEEE ICC 2024 Workshop - Edge5GMN, Denver (USA), June 2024
Contributo in Atti di Convegno (Proceeding) - Malandrino, F.; Di Giacomo, G.; Levorato, M.; Chiasserini, C. F. (2024)
Dependable Distributed Training of Compressed Machine Learning Models. In: IEEE WoWMoM 2024, Perth (Australia), June 2024
Contributo in Atti di Convegno (Proceeding) - DI GIACOMO, Giuseppe; Franzese, Giulio; Cerquitelli, Tania; Chiasserini, Carla Fabiana; ... (2023)
Multi-View Latent Diffusion. In: 2023 IEEE International Conference on Big Data, Salerno (Italy), December 2023
Contributo in Atti di Convegno (Proceeding) - Malandrino, Francesco; Di Giacomo, Giuseppe; Karamzade, Armin; Levorato, Marco; ... (2023)
Tuning DNN Model Compression to Resource and Data Availability in Cooperative Training. In: IEEE-ACM TRANSACTIONS ON NETWORKING, pp. 1-16. ISSN 1063-6692
Contributo su Rivista - Morra, Lia; Azzari, Alberto; Bergamasco, Letizia; Braga, Marco; Capogrosso, Luigi; ... (2023)
Designing Logic Tensor Networks for Visual Sudoku puzzle classification. In: 17th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2023), Certosa di Pontignano, Siena (Italia), July 3-5, 2023, pp. 223-232. ISSN 1613-0073
Contributo in Atti di Convegno (Proceeding)