Arvin Ebrahimkhanlou
Papers
7
Total Citations
196
H-Index
4
About
Arvin Ebrahimkhanlou is a pioneering researcher at the intersection of structural health monitoring, robotics, and artificial intelligence, with a particular focus on the automated inspection and assessment of civil infrastructure. His landmark 2016 study on multifractal analysis of crack patterns in reinforced concrete shear walls — now amassing over 119 citations — established a rigorous computational framework for moving beyond subjective, manual inspection methods toward automated, camera-equipped robotic systems. Building on this foundation, Ebrahimkhanlou has developed multi-scale robotic methodologies that integrate cameras and LiDAR sensors for precise crack detection and measurement, addressing longstanding challenges in structural reliability assessment. His more recent contributions explore simultaneous localization and mapping (SLAM) techniques tailored for nondestructive evaluation, alongside innovative approaches for converting point cloud data into as-built wireframe digital twins to support autonomous robotic inspection workflows. Most recently, he has advanced the frontier by incorporating vision-language AI models for real-time defect detection, classification, and localization. Collectively, his work — spanning nearly a decade and accumulating close to 200 citations — offers transformative tools for making infrastructure inspection faster, more objective, and significantly more scalable.
Research Focus
Key Achievements
Top Papers
- 1Multifractal analysis of crack patterns in reinforced concrete shear walls119 citations · 2016
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