Muhammad Rakeh Saleem
Papers
2
Total Citations
75
H-Index
2
About
Muhammad Rakeem Saleem is a leading researcher in the intersection of civil infrastructure inspection, computer vision, and human-robot interaction. His primary contributions lie in developing automated, intelligent systems for structural health monitoring, with a specific focus on bridges and building facades. Saleem’s most impactful work, "Instant bridge visual inspection using an unmanned aerial vehicle by image capturing and geo-tagging system and deep convolutional neural network" (2020, 66 citations), pioneered a method to replace subjective, labor-intensive manual bridge inspections with a precise, automated UAV-based approach that quantifies and localizes damage. This work has become a foundational reference for integrating deep learning with drone technology in civil engineering. Further pushing the boundaries of the field, his research on "Analysis of gaze patterns during facade inspection to understand inspector sense-making processes" (2023) uses eye-tracking to decode expert visual strategies during inspections. This novel approach aims to imbue autonomous robots with a deeper, situation-aware understanding of structural defects, moving beyond simple damage detection toward replicating expert judgment. Through these innovations, Saleem is actively shaping a future where infrastructure inspection is safer, faster, and more objective.
Research Focus
Key Achievements
Top Papers
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