Background:

Xiao Pan is a Ph.D. candidate in Structural and Earthquake Engineering at The University of British Columbia (UBC). His own research is directed at data-driven structural health monitoring (SHM) and structural dynamic testing using AI, computer vision and 3D scanning techniques, as well as automated construction methods for civil structures. In 2016, Xiao obtained his two Bachelor’s Degrees (with First Class Honors) in Civil Engineering from the National University of Ireland, and Jiangnan University (China), where he achieved the 1st place in each academic year and received various awards such as the China National Award for Outstanding Undergraduates, University First-Class Honors Awards in both two universities. He received the Master of Science (MSc) Degree in general structural engineering with First-Class Honors (distinction standard) at Imperial College London in 2017. Further, Xiao joined UBC as a Ph.D. student, where Xiao has achieved a GPA of 93/100 in his course program, and received multiple awards including the President’s Academic Excellence Initiative PhD Award, Civil Excellence Award, Faculty of Applied Science Graduate Award.

 

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Research interests:

  • Structural health monitoring
  • 2D/3D computer vision
  • Machine learning and deep learning
  • 3D point cloud processing
  • Automated/robotic construction
  • Advanced numerical analysis and experimental testing of structures

 

Ph.D. research projects:

Xiao Pan is leading the AI team within the Smart Structures Group at UBC. His research is focused on the development and application of deep learning, computer vision, and robotic technologies for structural health monitoring, automated construction, and advanced testing [1]. He has developed an end-to-end automated assessment framework for post-disaster damage detection and loss estimation of civil structures, which consists of novel damage classification, localization, and quantification, as well as the performance-based earthquake engineering methodology for loss estimation [2]. Within the framework, novel damage detection methods have been developed for different structural systems and components. He developed detection-tracking pipeline for real-time bolt loosening monitoring and quantification [3]. More recently, for the first time, he has developed a 3D vision pipeline to create a 3D digital twin of structures using accurate and low-cost 3D computer vision methods, which can be used to detect various types of structural damages concurrently, and quantify the in-plane and out-of-plane deformations [4]. In addition, Xiao has integrated vision methods with robotic technologies to facilitate automated navigation, mapping, data collection, and structural inspection [5][6]. On the other hand, Xiao is also developing vision-based structural vibration measurement approaches, to provide cheap, accurate, and real-time sensor feedback, which is crucial for vibration-based SHM and structural testing [7].

 

Contributions as a senior Ph.D. candidate in the Smart Structures Group and Department of Civil Engineering at UBC:

Apart from his own research, Xiao Pan has been proactively assisting his supervisor, Prof. Tony Yang, in managing and leading multiple tasks within UBC Smart Structures Group. He has been training and working with junior MASc and PhD students in various research projects, including vision-based SHM, vision-based structural testing, numerical analysis and experimental tests of novel honeycomb steel fuses, numerical analysis and experimental tests of steel corrugated panels, nonlinear shake table control, and hybrid simulation. Several research projects have been successfully published in prestigious journals or submitted as patents for innovative structural devices. Meanwhile, he has made major contributions and provided valuable inputs to the research supervisor in preparing several successful research grant proposals. Lastly, Xiao has been working as a teaching assistant in over 7 different graduate and undergraduate courses in the Department of Civil Engineering at UBC, where his main responsibilities include teaching, tutoring, and marking homework.

 

 

Outside research work:

Xiao Pan has been studying in four different countries including China, the Republic of Ireland, the UK, and Canada, and traveled to many places worldwide. He has served as vice director of the Mountain Bike Society at Jiangnan University in China. His main hobbies are hiking, travelling, and biking.

 

 

 

 

 

 

Journal Publications:

Pan, X., Yang, T. Y. (2022). 3D vision-based out-of-plane displacement quantification for steel plate structures using structure from motion, deep learning and point cloud processing. Computer-aided Civil and Infrastructure Engineering, http://doi.org/10.1111/mice.12906.

Xiao, Y., Pan, X., & Yang, T. Y. (2022)Nonlinear backstepping hierarchical control of shake table using high-gain observer, Earthquake Engineering & Structural Dynamicshttp://doi.org/10.1002/eqe.3726.

Pan, X., & Yang, T. Y. (2021). Image-based monitoring of bolt loosening through deep-learning-based integrated detection and tracking. Computer‐Aided Civil and Infrastructure Engineering, 1–16. https://doi.org/10.1111/mice.12797. 

Pan, X., & Yang, T. Y. (2020). Postdisaster image‐based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks. Computer‐Aided Civil and Infrastructure Engineering35(5), 495-510. 

Pan, X., & Málaga‐Chuquitaype, C. (2020). Seismic control of rocking structures via external resonators. Earthquake Engineering & Structural Dynamics49(12), 1180-1196. (Top Cited Article)

Yang, T. Y., Li, T., Tobber, L., & Pan, X. (2020). Experimental and numerical study of honeycomb structural fuses. Engineering Structures204, 109814.

Pan, X.Xiao, Y., Yao, H., Yang, T. Y., & Adeli, H. (2022). Vision-based real-time structural vibration measurement through interactive deep-learning-based detection and tracking methods. Engineering Structures. under review.

Tavasoli, S., Pan, X., Yang, T. Y. (2022). Vision-based autonomous navigation and indoor damage assessment of reinforced concrete buildings using low-cost drones and deep learning. Automation in Construction. under review.

Conference Publications:

Pan, X., Vaze, S., Xiao, Y., Tavasoli, S., Yang T.Y. “Structural damage detection of steel corrugated panels using computer vision and deep learning.” Canadian Society for Civil Engineering (CSCE) conference, 2022, Whistler, British Columbia, Canada. accepted.

Pan, X., Wen, Z., Yang T.Y. “Dynamic analysis of structures using artificial neural network with adaptive training.” 17th World Conference on Earthquake Engineering, 2021, Sendai, Japan.

Yang T.Y., Li, T., Tobber, L., Pan, X. “Experimental Test of Novel Honeycomb Structural Fuse.” 2019 International Conference on Steel and Composite Structures (ICSCS19).

arXiv:

Pan, X., & Yang, T. Y. (2021).Postdisaster image‐based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks. Computer Vision and Pattern RecognitionarXiv:2111.09862.

Pan, X., & Yang, T. Y. (2021). Image-based monitoring of bolt loosening through deep-learning-based integrated detection and tracking. Computer Vision and Pattern RecognitionarXiv preprint, arXiv:2111.09117.

Pan, X., Wen, Z., & Yang, T. Y. (2021).Dynamic analysis of nonlinear civil engineering structures using artificial neural network with adaptive trainingMachine LearningarXiv: 2111.13759.

 

Domestic/International Presentations:

[1]. 3D computer vision technologies for structural damage detection. The 2022 Forum of “Hongshen Young Scholars”, Chongqing University, 2022, Chongqing, China.

[2]. Structural damage detection of steel corrugated panels using computer vision and deep learning. Canadian Society for Civil Engineering (CSCE) conference, 2022, Whistler, British Columbia, Canada.

[3]. Development and application of CNN-based vision methods for structural damage detection. The 7th Forum of “Yanta Scholars”, 2021, Xi’an, China.

[4]. Development of Artificial Neural Networks with Adaptive Training for Structural Dynamic Analysis. 17th World Conference on Earthquake Engineering (17th WCEE), 2021, Sendai, Japan.

[5]. Development and Application of Vision-based Technologies for Structural Condition Assessment. 2nd China-Canada Symposium on Structural & Earthquake Engineering (2nd CCSSEE), 2019, Guangzhou, China.

[6]. Vison-based Structural Damage Detection for Reinforced Concrete Structures, 7th Tongji-UBC Symposium on Earthquake Engineering, 2019, Shanghai, China.

 

 

 

Awards:

2022 Top Cited Article Award, Journal of Earthquake Engineering & Structural Dynamics (JCR Q1, top journal).

2020-2022   President’s Academic Excellence Initiative PhD Award, UBC, Canada.

2019   Civil Engineering PhD Excellence Award, UBC, Canada.

2018-Present  International Tuition Award, UBC, Canada.

2016   Tobin Gold Medal, Tobin Consulting Engineers, Ireland.

2016   Ward and Burke Medal, Ward & Burke Construction Ltd, Ireland.

2016   University Research Scholarship for Undergraduates, NUI Galway, Ireland.

2015-2016   First Class Honours Award, NUI Galway, Ireland.

2015   RPS Consulting Engineers Prize, RPS Group, Ireland.

2014   University Tuition Fees Scholarship (40% deduction), NUI Galway, Ireland.

2014   China’s National Scholarship for Outstanding Undergraduates, Educational Ministry of China.

2013/2014 University First-prize Award to Excellent Undergraduate Students, Jiangnan University, China.