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About

Giacomo Nabissi is a researcher specializing in human-robot interaction, industrial robotics, predictive maintenance, and intelligent condition monitoring systems — fields that sit at the intersection of automation, machine learning, and Industry 4.0. His most influential contribution, a 2021 survey on human-robot perception in industrial environments (152 citations), established him as a leading voice in understanding how autonomous and collaborative robots can safely and effectively operate alongside humans in complex manufacturing settings. Beyond perception, Nabissi has made substantial contributions to the reliability and health management of industrial systems, developing predictive maintenance frameworks that leverage motor current signal analysis and torque diagnostics to detect faults in Permanent Magnet Synchronous Motors under both stationary and transient conditions. His 2023 work on anomaly detection and concept drift adaptation for collaborative robots (23 citations) reflects a growing focus on building intelligent, self-updating diagnostic systems capable of handling dynamic real-world environments. He has also contributed practical, software-driven solutions, including a ROS-based condition monitoring architecture for automatic fault detection in cobots. Collectively, his research addresses one of modern manufacturing's most pressing challenges: ensuring that increasingly autonomous robotic systems remain safe, efficient, and resilient across their operational lifetimes.