Associate Professor, ROC Military Academy, Taiwan
Ching-Lung Fan is an associate professor in Civil Engineering at the Republic of China Military Academy. He completed his Ph.D. in 2019 from the National Kaohsiung University of Science and Technology. His professional journey reflects a strong dedication to advancing technology in the construction and civil engineering sectors, particularly through the application of machine learning and deep learning methods. 🏫
Publication Profile
Education
Dr. Fan holds a Master of Science (M.S.) from National Taiwan University (2006) and a Ph.D. from National Kaohsiung University of Science and Technology (2019). His academic background underscores his commitment to both theoretical and practical contributions to the field. 🎓
Experience
Dr. Fan started his academic career as an assistant professor at the Republic of China Military Academy in January 2019 and was promoted to associate professor in June 2022. His teaching and research experience has significantly impacted the study of civil engineering, especially through the integration of machine learning and data mining. 🏢
Awards and Honors
Ching-Lung Fan has received several prestigious awards, including the Phi Tau Phi Scholastic Honor (2019), Outstanding Paper Award (2021), Excellent Paper Award (2022), and Best Researcher Award (2024). In 2023, he was honored with membership in Sigma Xi, an esteemed scientific organization. 🏅
Research Focus
Dr. Fan’s research interests are primarily centered around machine learning, deep learning, data mining, construction performance evaluation, and risk management. His work integrates cutting-edge computational methods with civil engineering applications to enhance the quality and efficiency of construction projects. 🤖📊
Conclusion
Dr. Fan’s innovative contributions to civil engineering, particularly in the realm of AI-driven solutions, continue to shape the future of construction and infrastructure development. His ongoing research and recognition in the academic community highlight his expertise and impact in the field. 🌟
Publications
Integrating image processing technology and deep learning to identify crops in UAV orthoimages. CMC-Computers, Materials & Continua. (Accepted).
Predicting the construction quality of projects by using hybrid soft computing techniques. CMES-Computer Modeling in Engineering & Sciences. (Accepted).
Evaluation model for crack detection with deep learning—Improved confusion matrix based on linear features. Journal of Construction Engineering and Management (ASCE), 151(3): 04024210. (SCI).
Evaluating the performance of Taiwan airport renovation projects: An application of multiple attributes intelligent decision analysis. Buildings, 14(10): 3314. (SCI).
Deep neural networks for automated damage classification in image-based visual data of reinforced concrete structures. Heliyon, 10(19): e38104. (SCI).
Multiscale feature extraction by using convolutional neural network: Extraction of objects from multiresolution images of urban areas. ISPRS International Journal of GeoInformation, 13(1): 5. (SCI).
Ground surface structure classification using UAV remote sensing images and machine learning algorithms. Applied Geomatics, 15: 919-931. (ESCI).
Using convolutional neural networks to identify illegal roofs from unmanned aerial vehicle images. Architectural Engineering and Design Management, 20(2): 390-410. (SCI).
Evaluation of machine learning in recognizing images of reinforced concrete damage. Multimedia Tools and Applications, 82: 30221-30246. (SCI).
Supervised machine learning–Based detection of concrete efflorescence. Symmetry, 14(11): 284. (SCI).