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dr. X. Yin (Xianfei)

Assistant Professor

About Me

My research focused on the improvement of civil infrastructure maintenance management, smart infrastructure construction, smart city development, and information integration/visualization for buildings and construction process (such as Building Information Modelling), drawing upon knowledge in the domains of artificial intelligence, advanced data analytics, simulation modelling, decision support system and construction project management. 

Expertise

Engineering & Materials Science
Defects
Inspection
Networks (Circuits)
Pipe
Prefabricated Construction
Productivity
Sewers
Television

Publications

Recent
Yuan, M., Li, Z., Li, X., Luo, X. , Yin, X., & Cai, J. (2021). Proposing a multifaceted model for adopting prefabricated construction technology in the construction industry. Engineering, Construction and Architectural Management. https://doi.org/10.1108/ECAM-07-2021-0613
Yin, X., Chen, Y., Bouferguene, A., Zaman, H., Al-Hussein, M., & Kurach, L. (2020). A deep learning-based framework for an automated defect detection system for sewer pipes. Automation in construction, 109, [102967]. https://doi.org/10.1016/j.autcon.2019.102967
Chen, Y., Bouferguene, A., Shen, Y. , Yin, X., & Al-Hussein, M. (2020). Bilevel Decision-Support Model for Bus-Route Optimization and Accessibility Improvement for Seniors. Journal of computing in civil engineering, 34(2), [04019057]. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000875
Yin, X., Liu, H., Chen, Y., Wang, Y., & Al-Hussein, M. (2020). A BIM-based framework for operation and maintenance of utility tunnels. Tunnelling and underground space technology, 97, [103252]. https://doi.org/10.1016/j.tust.2019.103252
Yin, X., Chen, Y., Bouferguene, A., & Al-Hussein, M. (2020). Data-driven bi-level sewer pipe deterioration model: Design and analysis. Automation in construction, 116, [103181]. https://doi.org/10.1016/j.autcon.2020.103181
Yin, X., Chen, Y., Bouferguene, A., Zaman, H., Al-Hussein, M., & Russell, R. (2020). Data-Driven Framework for Modeling Productivity of Closed-Circuit Television Recording Process for Sewer Pipes. Journal of construction engineering and management, 146(8), [04020093]. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001885
Yin, X., Bouferguene, A., & Al-Hussein, M. (2020). Data-Driven Sewer Pipe Data Random Generation and Validation. Journal of construction engineering and management, 146(12), [04020131]. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001937

UT Research Information System

Google Scholar Link

Affiliated Study Programmes

Bachelor

Master

Courses Academic Year  2021/2022

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
 

Contact Details

Visiting Address

University of Twente
Faculty of Engineering Technology
Horst Complex (building no. 20), room Z208
De Horst 2
7522LW  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Engineering Technology
Horst Complex  Z208
P.O. Box 217
7500 AE Enschede
The Netherlands