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About

Matteo Menolotto is a leading researcher at the intersection of human-robot interaction, industrial automation, and biomechanics. His work focuses on advancing Industry 4.0 by developing safer, more intuitive collaborative robotics systems and understanding human physical capabilities. Menolotto’s most influential contribution is his comprehensive systematic review on motion capture technology in industrial applications (2020), which has garnered 292 citations and serves as a foundational resource for integrating advanced sensing solutions into manufacturing. He has also made significant strides in human-robot trust, investigating how interface design impacts operator confidence and collaboration efficiency. His research extends to biomechanics, where he developed models to estimate maximum shoulder and elbow joint torques based on demographics and anthropometrics, aiding in the prevention of musculoskeletal disorders. Additionally, Menolotto has addressed critical safety challenges in human-robot collaboration by quantifying latency cascades and time-to-respond dynamics for speed and separation monitoring. His work is essential for creating ergonomic, trustworthy, and safe industrial environments where humans and robots work seamlessly together.