| Biography | |
|---|---|
 Prof. Young-Jin Cha University of Manitoba, USA |
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| Title: Structural Health Monitoring with advanced deep learning and autonomous UAVs. | |
| Abstract: This online seminar provides deep learning-based structural health monitoring from crack classification, multiple types of damage classification, volumetric quantification of concrete spalling, crack segmentation, autonomous UAV methods, and their integrations. This presentation introduces deep learning-based approaches for structural health monitoring (SHM) applications. It will introduce a convolutional neural network (CNN) based crack classification, and a faster based CNN (faster R-CNN) based multiple types of damage detection for civil infrastructures to detect and localize the detected damage using bounding boxes. The faster R-CNN was also applied for concrete spalling damage detection for volumetric quantification using depth camera. Autonomous flight method of UAV is introduced to integrate it with deep learning-based damage detection. Subsurface damage detection is introduced using deep learning and thermography. Damage segmentation methods (SDDNet and STRNet) are introduced to detect cracks in pixel level in complex background scenes with real-time manner. These advanced deep learning-based methods overcome the limitation of traditional computer vision-based methods. It also opened the new door for fully automated SHM. | |
| Biography: Professor Young-Jin Cha received his Ph.D. (2008) from Texas A&M University in the Department of Civil and Environmental Engineering. He became post-doctoral associate at the Massachusetts Institute of Technology (MIT) (2012). He then joined the Department of Civil Engineering at the University of Manitoba in 2014. His extensive research activities in the Structural Health Monitoring and structural control for seismic damage reduction have led to the publication of 41 journal articles, 39 conference papers and 68 presentations. His key scientific contribution is deep learning-based automated SHM with autonomous Unmanned Aerial Vehicles. He brought this topic to light with paper publications in top-ranking journals. Researchers, professors including scientists, students, and industry professionals from many different countries have been showing strong interest in this innovative topic since 2016. According to Google Scholar, he has received 3,929 citations, 962 of which were received during the last year 2020. He was reported as top 0.65% cited scientist for single-year impact in the world within Civil Engineering field in 2020 from Mendeley.com. He was named to 2005 Who’s Who in America. He is serving as core peer-reviewers and Editorial Board Members in many top engineering journals associated with IEEE, Elsevier, and ASCE. | |
