Giuseppe Di Giacomo

Dottorando in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 37o ciclo (2021-2024)
Dipartimento di Elettronica e Telecomunicazioni (DET)

Borsista (BE)
Studenti, Didattica e Internazionalizzazione (STUDI)

Profilo

Dottorato di ricerca

Argomento di ricerca

Distributed Machine Learning

Tutori

Interessi di ricerca

Big Data, Machine Learning, Neural Networks and Data Science
Communication and Computer Networks

Biografia

Giuseppe Di Giacomo was born in Turin (Italy) on June 11th, 1996.
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, G.; Franzese, G.; Cerquitelli, T.; Chiasserini, C. F.; Michiardi, P. (2024)
    DiMViDA: Diffusion-based Multi-View Data Augmentation. In: 2024 IEEE 29th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Athens (Greece), Oct. 2024
    Contributo in Atti di Convegno (Proceeding)
  • DI GIACOMO, Giuseppe; Franzese, Giulio; Cerquitelli, Tania; Chiasserini, Carla Fabiana; ... (2024)
    DiMViS: Diffusion-based Multi-View Synthesis. In: ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling 2nd SPIGM @ ICML, Vienna (Austria), July 2024
    Contributo in Atti di Convegno (Proceeding)
  • 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), 04-07 June 2024. ISBN: 979-8-3503-9466-5
    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, Sorrento (Italy), 15-18 December 2023. ISBN: 979-8-3503-2445-7
    Contributo in Atti di Convegno (Proceeding)