Lucrezia Morabito

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About

Lucrezia Morabito is a leading researcher at the intersection of cloud, fog, and edge computing, with a focused expertise in enabling predictive analytics for industrial cyber-physical systems. Her work is fundamentally reshaping how data is managed and processed in manufacturing environments, moving from reactive maintenance to proactive, data-driven strategies. Morabito’s major contributions center on architecting distributed computing frameworks—specifically, her pioneering "cloud-to-edge" and "fog computing" approaches—that allow for real-time anomaly detection and failure prediction directly on the factory floor. Her most influential work, "A Cloud-to-Edge Approach to Support Predictive Analytics in Robotics Industry" (2020), has garnered 46 citations, establishing her as a key voice in the field. This research, along with her subsequent studies on fog-based predictive maintenance (17 citations) and cloud-to-edge architectures (11 citations), demonstrates a clear trajectory toward creating more resilient and intelligent production systems. By enabling the discovery of criticalities and the prediction of imminent failures, Morabito’s work is not only advancing academic knowledge but also providing tangible solutions for the next generation of smart, autonomous industry.