Shakiba Davari
Papers
2
Total Citations
235
H-Index
2
About
Shakiba Davari is a leading researcher at the intersection of computer vision, robotics, and construction engineering. Her work focuses on automating the capture and analysis of physical construction sites to bridge the gap between real-world conditions and digital building information models (BIM). Davari’s most influential contribution is her pioneering work on automated computer vision-based detection of under-construction indoor partitions, a paper that has garnered over 203 citations and laid the foundation for real-time progress monitoring on job sites. She further advanced the field by developing UAV-enabled site-to-BIM automation, creating aerial robotic and computer vision pipelines that generate as-built BIM models and enable quality control—a critical step toward fully autonomous construction inspection. Her research directly addresses the persistent challenge of integrating reality capture data with digital twins, significantly improving the accuracy and efficiency of facility management and construction oversight. Davari’s work is essential reading for students and researchers in construction informatics, robotics, and applied computer vision, demonstrating how automated sensing can transform traditional building practices into data-driven, intelligent processes.
Research Focus
Key Achievements
Top Papers
- 1
- 2