Feryel Zoghlami

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About

Feryel Zoghlami is a researcher at the forefront of industrial automation and human-robot collaboration, with a focus on enhancing safety and efficiency in smart manufacturing environments. Her work bridges the gap between advanced sensing technologies and practical factory automation, particularly within the Industry 4.0 framework. Zoghlami’s most cited paper, “ToF/Radar early feature-based fusion system for human detection and tracking” (2021, 18 citations), introduces a novel multi-sensor approach that combines Time-of-Flight and radar data to reliably detect and track human workers in dynamic industrial settings—a critical contribution to safe human-robot interaction. Her 2019 paper, “The Long Journey From Standardization to Fully Fab Automation and More” (8 citations), offers valuable insights into the real-world challenges of transitioning a mature fabrication facility to full automation, including change management strategies. Zoghlami’s work is notable for its practical impact, addressing the persistent need for human presence in automated production lines while leveraging cutting-edge sensor fusion to guide robotic systems. Her research continues to influence the development of safer, more adaptive industrial environments.