Enabling Edge-based Federated Learning through MQTT and OMA Lightweight-M2M. - Giacomo Genovese; Gurtaj Singh; Claudia Campolo; Antonella Molinaro (VTC Spring, 2022)

Machine Learning Performance at the Edge: When to Offload an Inference Task. - Olga Chukhno; Gurtaj Singh; Claudia Campolo; Antonella Molinaro; Carla-Fabiana Chiasserini (NET4us@MobiCom, 2023)

Federated Learning to Safeguard Patients Data: A Medical Image Retrieval Case. - Gurtaj Singh; Vincenzo Violi; Marco Fisichella (Big Data Cogn. Comput., 2023)

Scalable and interoperable edge-based federated learning in IoT contexts. - Claudia Campolo; Giacomo Genovese; Gurtaj Singh; Antonella Molinaro (Comput. Networks, 2023)

Compressing and Fine-tuning DNNs for Efficient Inference in Mobile Device-Edge Continuum. - Gurtaj Singh; Olga Chukhno; Claudia Campolo; Antonella Molinaro; Carla-Fabiana Chiasserini (MeditCom, 2024)

Poster: Digital Twins for Personalized and Safer Automated Driving. - Claudia Campolo; Nadia Mammone; Antonella Molinaro; Bruno Pizzimenti; Gurtaj Singh; Domenico Mario Zappalà (VNC, 2024)

Mitigating the Communication Straggler Effect in Federated Learning via Named Data Networking. - Marica Amadeo; Claudia Campolo; Antonella Molinaro; Giuseppe Ruggeri; Gurtaj Singh (IEEE Commun. Mag., 2024)

In-Network Edge Split Inference via Named Data Networking. - Marica Amadeo; Claudia Campolo; Antonella Molinaro; Giuseppe Ruggeri; Gurtaj Singh (NetSoft, 2025)

Digital Twin-assisted Context-aware Object Detection for Connected and Automated Vehicles. - Claudia Campolo; Antonella Molinaro; Bruno Pizzimenti; Gurtaj Singh; Domenico Mario Zappalà (VNC, 2025)