Yue Chen | Structure Fatigue | Research Excellence Award

Prof. Dr. Yue Chen | Structure Fatigue | Research Excellence Award

Professor | Chongqing jiaotong University | China

Prof. Dr. Yue Chen is an Associate Professor in the field of structural engineering, with recognized expertise in fatigue behavior, damage detection, and reliability assessment of steel and concrete structures. Her research focuses on fatigue performance of welded steel components, early damage identification using metal magnetic memory technology, artificial intelligence–based fatigue reliability analysis, and performance enhancement of in-service bridges, alongside contributions to seismic structural design. She has published more than 35 peer-reviewed journal articles in international and national journals and has received multiple provincial- and ministerial-level science and technology awards, reflecting the quality and impact of her work. She has led several competitive research projects funded by national and regional agencies and actively collaborates with multidisciplinary research teams. Her studies provide practical methodologies for structural health monitoring and infrastructure safety management, offering meaningful societal impact by supporting the durability, resilience, and sustainable operation of critical engineering structures worldwide.

Citation Metrics (Scopus)

100

75

50

25

0

Citations
90

Documents
21

h-index
6


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Top 5 Publications

Maloth Naresh | Structural Health Monitoring | Best Researcher Award

Dr. Maloth Naresh | Structural Health Monitoring | Best Researcher Award

Assistant Professor | Sharad Institute of Technology College of Engineering Yadrav | India

Dr. Maloth Naresh is an accomplished researcher and academic in Structural Engineering, specializing in data-driven and machine learning applications for Structural Health Monitoring (SHM) of steel frame structures. He earned his Ph.D. from the National Institute of Technology Hamirpur in 2024, where his doctoral research focused on developing advanced machine learning algorithms to monitor, predict, and assess joint damages in steel structures under varying environmental and operational conditions. With a strong publication record in high-impact SCI and SCIE-indexed journals such as Smart Materials and Structures, Strain (Wiley), and Asian Journal of Civil Engineering, Dr. Naresh has significantly contributed to the intersection of civil engineering and computational intelligence. His works on CNN–LSTM-based hybrid models and optimized SVM frameworks have advanced precision in damage detection, enabling early prediction and maintenance optimization in complex infrastructure systems. Recognized among the top-cited authors by Strain for 2023, his research demonstrates both academic excellence and practical relevance. He has presented papers at reputed international conferences including NIT Silchar and IIT Hyderabad and has also submitted a national-level research proposal under the NSTMIS scheme. Currently serving as Head of the Civil Engineering Department at Sharad Institute of Technology College of Engineering, Maharashtra, he fosters research collaborations with scholars from NIT Hamirpur, NIT Sikkim, and the University of Huddersfield (UK), emphasizing global partnerships and interdisciplinary innovation. His technical expertise spans MATLAB programming, ANSYS modeling, AutoCAD design, and advanced data analysis in structural dynamics. Dr. Naresh’s academic journey is marked by consistent excellence, including qualifying GATE 2015 and earning an HRD Scholarship from the Government of India. With nine high-quality publications and growing recognition across the research community, he continues to expand his scholarly impact through innovative methodologies that enhance the reliability, sustainability, and safety of civil infrastructure systems worldwide.

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