Marco Becattini

Papers

Total Citations

H-Index

About

Marco Becattini is a leading researcher at the intersection of network softwarization and industrial digitalization, with a primary focus on Network Digital Twins (NDTs) and resource management for ultra-reliable low-latency communications (URLLC). His work addresses the growing complexity of modern networks, driven by the proliferation of IoT devices, edge computing, and distributed algorithms. Becattini’s major contributions include pioneering systematic frameworks for NDTs, which enable real-time network simulation, monitoring, and optimization. His 2024 paper, "Network Digital Twins: A Systematic Review," has already garnered 11 citations, establishing a foundational taxonomy for this emerging field. In parallel, his research on dynamic MEC resource allocation for Industry X.0 scenarios—such as AR/VR and autonomous robotics—provides quantitative, digital-twin-driven solutions to ensure URLLC in demanding industrial environments. Though early in his career, Becattini’s work is notable for bridging theoretical network models with practical, high-stakes applications, directly impacting the design of future smart factories and critical infrastructure. His achievements highlight a clear trajectory toward shaping next-generation, self-optimizing networks.