Papers
3
Total Citations
28
H-Index
2
About
M. Savino is a researcher at the forefront of industrial ergonomics and human-robot collaboration, leveraging computer vision and machine learning to prevent work-related musculoskeletal disorders (WMSDs). Their key contributions lie in developing automated ergonomic risk assessment systems that use 3D human pose estimation to analyze worker postures in real time. By integrating these assessments with collaborative robots, Savino’s work enables safer, more adaptive manufacturing environments—a critical advancement for Industry 4.0. Their most-cited paper, “An Ergonomic Risk Assessment System Based on 3D Human Pose Estimation and Collaborative Robot” (2024), has already garnered 17 citations, reflecting its timely impact. Earlier foundational work includes a CNN-based passive optical range finder for real-time stereo vision (2002, 9 citations), which pioneered neural network approaches for autonomous robotics. Savino’s research not only advances technical methods for joint angle calculation from video but also offers practical solutions for optimizing workplace safety. Their ongoing efforts to merge ergonomic risk optimization with collaborative robotics mark a significant step toward intelligent, human-centered automation.
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