Gianluca Amprimo
Papers
1
Total Citations
19
H-Index
1
About
Gianluca Amprimo is a researcher at the forefront of applying computer vision and artificial intelligence to structural health monitoring (SHM). His work focuses on developing non-invasive, image-based methods to detect and assess deterioration in critical infrastructure, particularly cement-based structures. Amprimo’s most cited paper, a 2023 overview of computer vision and image processing in SHM, has garnered 19 citations, reflecting the growing urgency of his research area. He has made significant contributions by demonstrating how advanced algorithms can analyze visual data to identify early signs of material wear, cracks, and potential failure points—offering a safer, more cost-effective alternative to traditional inspection methods. Beyond SHM, Amprimo explores the intersection of AI and human motion analysis, contributing to rehabilitation and assistive technologies. His work is notable for bridging the gap between cutting-edge computational techniques and real-world engineering challenges, with implications for public safety and infrastructure resilience. For students and researchers, Amprimo’s research exemplifies how computer vision can transform passive monitoring into proactive hazard prevention.
Research Focus
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Top Papers
- 1