Erich Malan

Titolo della tesi

Distributed and Federated Learning over IoT networks

Argomento di ricerca

Distributed and Federated Learning over IoT networks

Tutori

• Andrea Calimera
• Enrico Macii

Presentazione della ricerca

Poster

• Certificate of attendance to conference as a speaker at the 31st IEEE International Conference on Electronics Circuits and Systems (ICECS), 2024. (2024)
• Certificate of presentation at the International Joint Conference on Neural Networks (IJCNN) 2025. (2025)
• Certificate of participation as a session chair at the conference IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC), 2025. Session chair for: 2025 IEEE COMPSAC International Workshop on Modeling and Verifying Distributed-Embedded Applications (MVDA 2025) 2025 IEEE International Workshop on Rising ICT Solutions for Smart Grids as Multi-energy Systems (ICT4SmartGrid 2025) (2025)
• Certificate of attendance to conference as a speaker at the IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC), 2025 (2025)
• Certificate of attendance to conference as a speaker at the IEEE International Symposium on Low Power Electronics and Design (ISLPED) 2023. (2023)
• PhD DAUIN Quality Award 2025 (2025)

Corso di laurea di 1° livello

• Informatica. A.A. 2025/26, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
• Informatica. A.A. 2024/25, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
• Informatica. A.A. 2023/24, INGEGNERIA INFORMATICA. Collaboratore del corso
• Informatica. A.A. 2022/23, INGEGNERIA INFORMATICA. Collaboratore del corso

• EDA - Electronic Design Automation (DAUIN)

• Malan, Erich; Peluso, Valentino; Calimera, Andrea; Macii, Enrico (2026)
  FedAGF: Adaptive Concurrency via Gradient Feedback for Mitigating Extreme Label Skew in Budget-Constrained Federated Learning. In: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS. I, REGULAR PAPERS, pp. 1-14. ISSN 1549-8328
  Contributo su Rivista
• Malan, Erich; Peluso, Valentino; Calimera, Andrea; Macii, Enrico (2026)
  Refined Two-Sided Learning Rate Tuning for Robust Evaluation in Federated Learning. In: IEEE TRANSACTIONS ON ARTIFICIAL INTELLIGENCE, vol. 7, pp. 906-917. ISSN 2691-4581
  Contributo su Rivista
• Malan, Erich; Peluso, Valentino; Calimera, Andrea; Macii, Enrico (2025)
  Gradient-Aware Participation for Energy Reduction in Federated Learning with Extreme Label Skew. In: International Joint Conference on Neural Networks (IJCNN), Rome (ITA), June 30-July 5, 2025. ISBN: 979-8-3315-1042-8
  Contributo in Atti di Convegno (Proceeding)
• Malan, Erich; De Vizia, Claudia; Castangia, Marco; Peluso, Valentino; Calimera, Andrea; ... (2025)
  Privacy-Preserving Federated Learning for Household Characteristic Identification. In: 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC), Toronto ON (CAN), 08-11 July 2025, pp. 2040-2045. ISBN: 979-8-3315-7434-5
  Contributo in Atti di Convegno (Proceeding)
• Malan, Erich; Peluso, Valentino; Calimera, Andrea; Macii, Enrico (2025)
  Adaptive Client Participation in Budget-Constrained Federated Learning with Extreme Label Skew. In: 2025 23rd IEEE Interregional NEWCAS Conference (NEWCAS), Paris (FRA), 22-25 June 2025, pp. 15-19. ISBN: 979-8-3315-3256-7
  Contributo in Atti di Convegno (Proceeding)