Papers
2
Total Citations
52
H-Index
2
About
Dr. Mengnan Shi is a leading researcher at the intersection of civil infrastructure, computer vision, and intelligent robotics, with a focus on automated construction and maintenance. Their work has pioneered the use of deep learning and sensor fusion for critical infrastructure inspection, most notably in the detection of pavement cracks under challenging nighttime conditions. By integrating infrared and visible imaging with advanced neural networks, Shi achieved pixel-level crack detection accuracy, a breakthrough published in 2024 that has already garnered 27 citations for its practical safety implications. In the domain of construction robotics, Shi developed dynamic hyperparameter tuning algorithms for path-tracking control of robotic rollers on earth-rock dam projects, addressing the extreme variability of complex construction environments. This 2022 work, with 25 citations, demonstrates a rare ability to translate theoretical control methods into field-deployable solutions. Shi’s contributions bridge the gap between high-level AI and low-level hardware control, making autonomous heavy machinery more reliable in real-world settings. Their research is essential reading for engineers and computer scientists working on smart infrastructure, autonomous construction, and vision-based non-destructive testing.
Research Focus
Key Achievements
Top Papers
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