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Qingyu Xian

I am a PhD candidate working in WP2 of SUBLIME, responsible for structural health monitoring (SHM). Specifically, I am working on the dynamic behavior monitoring of bridges, such as vibrations and displacements. According to my academic background and interests, I plan to explore image-based vibration/displacement monitoring. This is motivated by the high cost and limited flexibility of traditional sensor-based approaches. My research encompasses technologies such as deep learning, 3D reconstruction, and multi-modal fusion.

I majored in Civil Engineering for both my undergraduate and master’s degrees. During my master’s studies, my research focus was primarily on the classification and detection of engineering images, such as the cross-sectional images of tunnels. After graduating, I worked as an algorithm engineer at a Chinese publicly listed internet company for three years. As I had hoped, I successfully applied for a computer science Ph.D. position at the University of Twente. My research interests now revolve around the interdisciplinary field of structural health monitoring (SHM), computer vision, deep learning, and 3D reconstruction.

In SUBLIME I would like to achieve more cost-effective and convenient dynamic behavior monitoring of bridges. Sensor-based methods are costly, incur high maintenance expenses, and come with various limitations during usage. My goal is to explore the potential application value of new technologies such as deep learning and multi-modal algorithms in the field of Structural Health Monitoring (SHM). I plan to propose a bridge vibration/displacement monitoring solution based on vision algorithms to realize more convenient and accurate monitoring.

I am delighted to join this project, as it offers numerous unknowns and opportunities for exploration. Being able to pursue research in an area that genuinely interests me brings me great joy.

Location: University of Twente (UT)

Supervisors: Prof. Paul Havinga , Dr. Berend-Jan van der Zwaag

Start date: May 1, 2023

End date: April 30, 2027

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