Giovanni Menegozzo
Papers
3
Total Citations
30
H-Index
3
About
Giovanni Menegozzo is a researcher advancing intelligent robotic systems through data-driven modeling and gesture recognition. His work focuses on two key areas: surgical robotics and intelligent manufacturing. In surgical robotics, Menegozzo developed automatic gesture recognition systems using time delay neural networks and kinematic data, enabling objective evaluation of surgical skills and real-time feedback during complex procedures. His 2019 paper on this topic has garnered 20 citations, establishing a foundation for advanced assistance features in surgical robotic systems. He further refined this approach with joint-space metrics for automated gesture classification (2020, 6 citations), contributing to the goal of standardized surgical skill assessment. Extending his expertise to manufacturing, Menegozzo applied similar automatic process modeling techniques to intelligent manufacturing systems (2019, 4 citations), enabling error-prone step detection and mitigation strategy design. His work bridges the gap between low-level sensor data and high-level process understanding, with applications ranging from surgical training to industrial automation. Menegozzo's research demonstrates how neural network architectures can transform raw kinematic data into actionable insights for both medical and manufacturing domains.
Research Focus
Key Achievements
Top Papers
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