Hamza Ben Haj Ammar

Papers

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About

Hamza Ben Haj Ammar is a rising researcher at the intersection of telecommunications and advanced manufacturing, whose work is pioneering the use of 5G technology for precise indoor positioning. His key research areas include deep learning, 5G localization, and industrial automation. Ammar’s major contributions lie in demonstrating how convolutional neural networks (CNNs) can overcome the inherent challenges of 5G-based positioning in complex manufacturing environments—such as multipath interference and signal noise—to achieve the high accuracy required for digital twins and robot fleet management. His most cited work, "Deep learning-based 5G indoor positioning in a manufacturing environment" (2022, 6 citations), and its follow-up (2023, 4 citations) are among the first to validate that shared 5G hardware can deliver cost-efficient, reliable positioning without dedicated infrastructure. By proving that deep learning can unlock 5G’s potential for sub-meter accuracy, Ammar is enabling a new generation of smart factories where mobile robots and digital replicas operate seamlessly. His research is foundational for the Industry 4.0 vision, making him a notable voice in the future of industrial connectivity.