Ching-Lung Fan | Civil Engineering| Best Researcher Award

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Assoc Prof Dr. Ching-Lung Fan | Civil Engineering| Best Researcher Award

Associate Professor at Republic of China Military Academy, Taiwan

Dr. Ching-Lung Fan is a prolific researcher and academic with a focus on construction management and engineering. His work spans various topics, including defect risk assessment, data mining, machine learning, and deep learning applications in construction. He has published extensively in prestigious journals and conferences, showcasing his expertise and contributions to the field. Dr. Fan’s research is highly regarded for its innovative approach and practical relevance, making him a respected figure in the academic community.

Professional Profiles:

📚 Education:

Dr. Ching-Lung Fan has a strong academic background, with a Master’s degree from National Taiwan University, Taipei, which he obtained from September 2004 to July 2006. Building on this foundation, he pursued further studies and completed his Ph.D. at the National Kaohsiung University of Science and Technology, Kaohsiung, from September 2014 to January 2019. His educational achievements reflect his dedication to learning and his commitment to advancing his expertise in military affairs and education.

🗣️Work experience:

Dr. Ching-Lung Fan has a distinguished career in academia, specializing in military affairs and education. He began his tenure at the Republic of China Military Academy, Kaohsiung, as an Assistant Professor in January 2019, where he demonstrated exceptional teaching and research skills. In recognition of his contributions and expertise, Dr. Fan was promoted to the position of Associate Professor in June 2022. His dedication to military education and his commitment to excellence make him a valuable asset to the academy.

Interests:

Dr. Ching-Lung Fan has a keen interest in the fields of machine learning, data mining, and deep learning. These areas of study align closely with his academic and professional pursuits, as they offer innovative approaches to analyzing and interpreting complex data. His interest in these fields underscores his commitment to staying abreast of the latest advancements in technology and using them to enhance his research and teaching capabilities.

 

📚Publications :

Evaluation of CART, CHAID, and QUEST Algorithms: A Case Study of Construction Defects in Taiwan

Authors: CL Lin, CL Fan*

Journal: Journal of Asian Architecture and Building Engineering

Year: 2019

Citations: 91

Defect risk assessment using a hybrid machine learning method

Authors: CL Fan

Journal: Journal of Construction Engineering and Management

Year: 2020

Citations: 37

Examining Association between Construction Inspection Grades and Critical Defects Using Data Mining and Fuzzy Logic

Authors: CL Lin, CL Fan*

Journal: Journal of Civil Engineering and Management

Year: 2018

Citations: 20

Hybrid analytic hierarchy process–artificial neural network model for predicting the major risks and quality of Taiwanese construction projects

Authors: CL Lin, CL Fan*, BK Chen

Journal: Applied Sciences

Year: 2022

Citations: 16

Evaluation of classification for project features with machine learning algorithms

Authors: CL Fan

Journal: Symmetry

Year: 2022

Citations: 9

Detection of multidamage to reinforced concrete using support vector machine-based clustering from digital images

Authors: CL Fan

Journal: Structural Control and Health Monitoring

Year: 2021

Citations: 9

Design and optimization of CNN architecture to identify the types of damage imagery

Authors: CL Fan*, YJ Chung

Journal: Mathematics

Year: 2022

Citations: 7

Application of the ANP and fuzzy set to develop a construction quality index: A case study of Taiwan construction inspection

Authors: CL Fan

Journal: Journal of Intelligent & Fuzzy Systems

Year: 2020

Citations: 7

Data mining model for predicting the quality level and classification of construction projects

Authors: CL Fan

Journal: Journal of Intelligent & Fuzzy Systems

Year: 2021

Citations: 5

Decision Tree Analysis of the Relationship between Defects and Construction Inspection Grades

Authors: CL Lin, CL Fan*

Journal: International Journal of Materials, Mechanics and Manufacturing

Year: 2019

Citations: 3