Automated nondestructive evaluation of compressive strength of underground lining structure using hyperspectral imaging and deep neural networks
aShanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, 202163, China
bKey Laboratory of Geotechnical and Underground Engineering of Ministry of Education, Tongji University, Shanghai, 200092, China
cDepartment of Geotechnical Engineering, Tongji University, Shanghai, 200092, China
dQingdao Guoxin Second Jiaozhou Bay Subsea Tunnel Co., Ltd., Qingdao, 266530, China
* Corresponding author. Department of Geotechnical Engineering, Tongji University, Shanghai, 200092, China.
E-mail address:
zhoum@tongji.edu.cn (M. Zhou).
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Dr. Mingliang Zhou is an Associate Professor and Assistant Dean at College of Civil Engineering, Tongji University, China. Dr. Zhou earned his BA, MEng, and Ph.D. from University of Cambridge, UK. His research focuses on tunnel engineering safety and disaster prevention in water-rich fault fracture zones. The research findings have been incorporated into two industry standards and successfully applied in major infrastructure projects, including the Qingdao Jiaozhou Bay Second Subsea Tunnel and the China-Laos Railway. He has authored more than 80 journal and conference papers and co-authored the book "AI-enhanced Safety Evaluation for Tunnelling in Rock Engineering". He holds international roles, including Asian Chair of the ISSMGE Young Members Presidential Group and membership in ISSMGE Technical Committees TC309 and TC222. His industry-linked research has received recognition through awards such as the ISSMGE Bright Spark Lecture Award, ITA Product Innovation Award, and the Gold Medal at the Geneva International Invention Exhibition.
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