Yuqing Gao

Earthquake Engineering Research Institute

Papers

Total Citations

H-Index

About

Yuqing Gao is a leading researcher in the application of deep learning to civil and construction engineering, with a primary focus on computer vision and semantic segmentation for infrastructure monitoring. Her most-cited work, "Deep semantic segmentation for visual understanding on construction sites" (2021), has garnered over 70 citations, establishing her as a key contributor to the field of automated site analysis. Gao’s research bridges the gap between artificial intelligence and practical construction management, enabling real-time, pixel-level identification of materials, equipment, and workers from site imagery. This contribution is pivotal for enhancing safety, productivity, and progress tracking on complex job sites. Beyond her seminal paper, she has advanced methodologies for robust visual recognition under challenging environmental conditions, such as varying lighting and occlusion. Her work is widely recognized for its potential to transform traditional construction practices through intelligent automation, making her a sought-after collaborator in both academic and industry circles. Gao’s research continues to shape the future of smart construction, empowering engineers with data-driven tools for safer and more efficient project delivery.