Gurtaj Singh

According to our database, Gurtaj Singh authored at least 9 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Digital Twin-assisted Context-aware Object Detection for Connected and Automated Vehicles.

Claudia Campolo, Antonella Molinaro, Bruno Pizzimenti, Gurtaj Singh, Domenico Mario Zappalà

Proceedings of the IEEE Vehicular Networking Conference, 2025

In-Network Edge Split Inference via Named Data Networking.

Marica Amadeo, Claudia Campolo, Antonella Molinaro, Giuseppe Ruggeri, Gurtaj Singh

Proceedings of the 11th IEEE International Conference on Network Softwarization, 2025

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., November, 2024

Poster: Digital Twins for Personalized and Safer Automated Driving.

Claudia Campolo, Nadia Mammone, Antonella Molinaro, Bruno Pizzimenti, Gurtaj Singh, Domenico Mario Zappalà

Proceedings of the IEEE Vehicular Networking Conference, 2024

Compressing and Fine-tuning DNNs for Efficient Inference in Mobile Device-Edge Continuum.

Gurtaj Singh, Olga Chukhno, Claudia Campolo, Antonella Molinaro, Carla-Fabiana Chiasserini

Proceedings of the IEEE International Mediterranean Conference on Communications and Networking, 2024

2023

Scalable and interoperable edge-based federated learning in IoT contexts.

Claudia Campolo, Giacomo Genovese, Gurtaj Singh, Antonella Molinaro

Comput. Networks, March, 2023

Federated Learning to Safeguard Patients Data: A Medical Image Retrieval Case.

Gurtaj Singh, Vincenzo Violi, Marco Fisichella

Big Data Cogn. Comput., March, 2023

Machine Learning Performance at the Edge: When to Offload an Inference Task.

Olga Chukhno, Gurtaj Singh, Claudia Campolo, Antonella Molinaro, Carla-Fabiana Chiasserini

Proceedings of the 2nd Workshop on Networked Sensing Systems for a Sustainable Society, 2023

2022

Enabling Edge-based Federated Learning through MQTT and OMA Lightweight-M2M.

Giacomo Genovese, Gurtaj Singh, Claudia Campolo, Antonella Molinaro

Proceedings of the 95th IEEE Vehicular Technology Conference, 2022