Leonardo Scommegna

Papers

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About

Leonardo Scommegna is a rising researcher at the forefront of network management and digital twin technologies. His primary research areas center on network digital twins (NDTs), edge computing, and ultra-reliable low-latency communications (URLLC) for industrial applications. Scommegna’s major contribution lies in systematically advancing the concept of NDTs as a transformative tool for managing increasingly complex networks. His most-cited work, "Network Digital Twins: A Systematic Review" (2024), with 11 citations, provides a foundational framework for understanding how NDTs can address challenges from IoT proliferation and softwarized technologies. In a complementary study, "Dynamic MEC resource management for URLLC in Industry X.0 scenarios" (2024), he proposes a quantitative approach using digital twin networks to optimize mobile edge computing resources for latency-sensitive applications like augmented reality and autonomous robotics. Though early in his career, Scommegna’s work is notable for bridging theoretical NDT concepts with practical, data-driven solutions for Industry X.0, positioning him as a key voice in the evolution of intelligent, adaptive network infrastructures.