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Nationwide excellent dissertation award

已更新:2022年12月7日

I am excited to know that my PhD thesis was recently awarded the "excellent doctoral dissertation in the Hydraulic category" across the country. The award is extremely competitive. With so many people graduating with a Hydraulic-related degree each year, only 33 dissertations were qualified to enter the evaluation round, among which only 10 would finally be awarded. It is definitely a great honor and a huge recognition of my work to win such an award. My sincere gratitude to Prof. Donghai Liu from Tianjin University, who was my PhD supervisor and had played an important supportive role in pushing me to complete the work.


I passed my PhD defense and earned a doctoral degree in the summer of 2020. Title of my PhD research is "耦合BIM的长距离输水渠道无人机巡检与险情智能图像识别研究" (English title: BIM-assisted UAV Safety Inspection and Automated Visual Recognition of Hazards for Water Diversion Channel). The research systematically explores the theory and specific approaches to integrating unmanned aerial vehicle (UAV), building information modeling (BIM) and visual computing in the safety inspection and hazard recognition of water channels.

Overarching framework of the research, which covers the entire process of “Aerial image collection – BIM integration – Image preprocessing – Image recognition”.

Augmenting aerial inspection with digital contents retrieved from BIM.
Registration of aerial photographs with BIM to extract regions of interest for hazard detection.
Automated detection of slope damages from the collected aerial photographs.

Relevant Content

Interested readers can access the dissertation here:


Contents in the dissertation have also been published separately as journal papers:

[1] Chen, J., & Liu D. (2021). Detecting, extracting and classifying foreign objects in inter-basin channels to ensure water supply safety. Journal of Hydroinformatics, jh20211118. [Linkage]

[2] Chen, J., Liu, D., & Li, X. (2021). Extracting Water Channels from Aerial Videos based on Image-to-BIM Registration and Spatio-Temporal Continuity. Automation in Construction, 132, 103970. [Linkage]

[3] Chen, J., & Liu, D (2020). Bottom-up image detection of water channel slope damages based on superpixel segmentation and support vector machine. Advanced Engineering Informatics, 47, 101205. [Linkage]

[4] Chen, J., Liu, D., Li S., & Hu, D. (2019). Registering Georeferenced Photos to a Building Information Model to Extract Structures of Interest. Advanced Engineering Informatics, 42, 100937. [Linkage]

[5] Liu, D., Chen, J.,Hu D., & Zhang, Z. (2019). Dynamic BIM-Augmented UAV Safety Inspection for Water Diversion Project. Computers in Industry, 108, 163-177. [Linkage]

[6] Liu, D., Chen, J., Li, S., & Cui, W. (2018). An integrated visualization framework to support whole-process management of water pipeline safety. Automation in Construction, 89, 24-37. [Linkage]

[7] Liu, D., Xia, X., Chen, J., & Li, S. (2021). Integrating Building Information Model and Augmented Reality for Drone-Based Building Inspection. Journal of Computing in Civil Engineering, 35(2), 04020073. [Linkage]



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