Fucai Li | Structural Health Monitoring and Fault Diagnosis | Best Researcher Award

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Dr. Fucai Li | Structural Health Monitoring and Fault Diagnosis | Best Researcher Award

Prof. Fucai Li is a distinguished academic at Shanghai Jiao Tong University 🇨🇳, specializing in vibration and ultrasonic signal processing, structural health monitoring, and intelligent sensor systems 🔍. With extensive global research experience across China 🇨🇳, Japan 🇯🇵, and Australia 🇦🇺, he has significantly contributed to mechanical engineering through innovative diagnostics and smart material systems 🛠️. He has published over 150 peer-reviewed papers and led numerous national and industrial research projects 📚🔬. His work bridges academia and industry, with collaborations involving giants like Bao Steel and Shanghai Electric ⚙️.

Profile

Education 🎓

Prof. Li earned his Ph.D. in Engineering from Xi’an Jiaotong University in 2003 🎓, where he also completed his Bachelor’s degree in Mechanical Engineering in 1998 🏫. His strong academic foundation from one of China’s premier technical universities laid the groundwork for a career focused on high-impact research 🧠. Throughout his education, he developed core expertise in mechanics, signal processing, and automation, setting the stage for innovations in sensor technologies and structural diagnostics 📡🔧.

Experience 👨‍🏫

Prof. Li currently serves as Professor at Shanghai Jiao Tong University (2015–present) 🏫. He was an Associate Professor there from 2009–2015 and held earlier roles including Assistant Professor (2003–2005) 🎓. His international experience includes research fellowships in Japan (JSPS, University of Tokyo, 2007–2009) 🇯🇵 and Australia (University of Sydney, 2005–2007) 🇦🇺. This global exposure enriched his expertise in structural innovation and smart systems 🌐. Across academia, he has shaped future engineers and researchers with cutting-edge knowledge and practical application insights 📘🔍.

Awards & Recognitions 🏅

Prof. Li has secured over 30 research grants from top national bodies like NSFC, Ministry of Science and Technology, and major industries including Bao Steel and Shanghai Electric 💼💡. He is widely recognized for his pioneering work in structural health monitoring and has published more than 150 influential journal papers 📑. His contributions to smart sensor networks and machine diagnostics have earned him national acclaim and trust from key industrial stakeholders 🤝. Through sustained innovation and impact, he has built a legacy of excellence in engineering research and collaboration 🏅.

Research Interests 🔬

Prof. Li’s research targets intelligent diagnostics and health monitoring of mechanical systems 🤖. His focus areas include vibration and ultrasonic signal analysis, fiber optic and piezo-electric sensor networks, and AI-driven fault detection systems 📊📡. He develops smart sensing technologies for predictive maintenance and infrastructure resilience, with applications ranging from aerospace to heavy machinery 🏗️✈️. His work integrates signal processing, materials science, and systems engineering to enable next-gen monitoring solutions. With over 150 publications and extensive funding, his research continues to push the frontier of smart mechanical engineering 🚀.

Publications 

Mingshuna Shun Jiang | Intelligent Sensors and Detection Technology | Best Researcher Award

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Prof. Mingshuna Shun Jiang | Intelligent Sensors and Detection Technology | Best Researcher Award

Mingshun Jiang is a professor at the School of Control Science and Engineering, Shandong University 🎓. He is a doctoral supervisor and a young expert of Mount Taishan Scholars 🌟. He serves as the director of the Shandong Engineering Research Center for Intelligent Sensor and Detection Technology 🔬 and deputy director of the Institute of Intelligent Perception 🏛️. His research primarily focuses on intelligent sensors and detection technologies, with over 20 funded projects, including the National Natural Science Foundation and the National Key R&D Program 🏆. He has authored 60+ high-level academic papers in renowned journals 📑. His innovative contributions aim at monitoring complex structural states in high-end equipment 🚀. With extensive industry collaborations, his work has applications in aerospace, rail transit, and military technology 🛰️🚆.

Profile

Education 🎓

Mingshun Jiang earned his doctoral degree in Control Science and Engineering from Shandong University 🎓. His academic journey focused on developing intelligent sensor systems and detection methodologies 📡. His research expertise was cultivated through interdisciplinary learning, integrating control science, artificial intelligence, and structural health monitoring 🤖. His doctoral research emphasized advanced ultrasonic-guided wave detection and probabilistic diagnostic imaging techniques 🏗️. Jiang’s educational background provided him with expertise in designing smart sensor networks, optimizing detection mechanisms, and enhancing structural health monitoring systems ⚙️. With strong mathematical and engineering foundations, he developed novel algorithms for real-time damage localization and predictive maintenance 📊. His continuous learning and research efforts have been instrumental in bridging technological gaps in aerospace, rail transit, and high-end industrial applications 🚆✈️.

Experience 👨‍🏫

Mingshun Jiang has extensive research and academic experience, currently serving as a professor at Shandong University 🏛️. He has led over 20 major research projects, including the National Natural Science Foundation and National Key R&D Program 🌍. As the director of the Shandong Engineering Research Center, he focuses on intelligent sensor development and detection technologies 🔍. His research has been successfully applied in aerospace, rail transit, and high-end industrial monitoring 🚀🚆. He has supervised numerous doctoral students and collaborated with various enterprises on engineering solutions 🏗️. Jiang has also played a key role in technical verification and real-world applications of his research findings 📡. His leadership in academia and industry-driven research has established him as a leading expert in intelligent perception and structural health monitoring 🏆.

Awards & Recognitions 🏅

Mingshun Jiang has received multiple prestigious recognitions, including being a young expert of Mount Taishan Scholars in Shandong Province 🌟. His work has been supported by national and provincial funding agencies, highlighting his contributions to intelligent sensor technology 🏆. He has been awarded numerous grants under the National Natural Science Foundation and National Key R&D Program 🎖️. Jiang’s research achievements have been recognized through invited talks at leading academic conferences and industry collaborations 🤝. He has served as an executive director of the China Inspection and Testing Society, further solidifying his reputation in the field 🔬. His high-impact publications in top-tier journals have earned him accolades for innovation and research excellence 📑. Jiang continues to receive recognition for his contributions to the monitoring of complex structural states in high-end equipment 🚀.

Research Interests 🔬

Mingshun Jiang’s research focuses on intelligent sensors, structural health monitoring, and detection technology 📡. His work integrates artificial intelligence, probabilistic diagnostic imaging, and ultrasonic-guided wave techniques for real-time damage localization and predictive maintenance 🏗️. Jiang has developed innovative methodologies for monitoring key structural indicators such as boundary loads, damage detection, and component failures 🚆. His research aims to bridge the gap between technological innovation and application in aerospace, rail transit, and industrial monitoring 🛰️. His team has successfully engineered high-end monitoring systems that have undergone technical validation and real-world implementation 🔍. Jiang’s expertise extends to developing smart sensing layers for structural health monitoring, contributing to safer and more efficient industrial systems ⚙️. Through his interdisciplinary research, he continues to advance intelligent perception systems for next-generation monitoring applications 🚀.

Publications 
  • Ruijie Song, Lingyu Sun, Yumeng Gao, Juntao Wei, Chang Peng, Longqing Fan andMingshun Jiang*. Unsupervised temperature-compensated damage localization method based on damage to baseline autoencoder and delay-based probabilistic imaging. Mechanical Systems and Signal Processing, 230: 112649, 2025.
  • Hong Zhang ,Feiyu Teng , Juntao Wei , Shanshan Lv , Lei Zhang , Faye Zhang  and Mingshun Jiang*. Damage Location Method of Pipeline Structure by Ultrasonic Guided Wave Based on Probability Fusion.  IEEE Transactions on Instrumentation and Measurement, 73, 9504914, 2024.
  • . LingyuSun , Juntao Wei , Chang Peng , Wei Hao , Feiyu Teng , Longqing Fan , Lei Zhang , Qingmei Sui  and Mingshun Jiang. Ultrasonic guided wave-based probabilistic diagnostic imaging method with Single-Path-Scattering sparse reconstruction for Multi-Damage detection in composite structures.  Mechanical Systems and Signal Processing, 223, 111858, 2024.
  • XiaoshuQin , Shanshan Lv , Changhang Xu , Jing Xie , Lei Jia , Qingmei Sui  and Mingshun Jiang*. Implications of liquid impurities filled in breaking cracks on nonlinear acoustic modulation response: Mechanisms, phenomena and potential applications.  Mechanical Systems and Signal Processing, 200, 110550, 2023.
  • Shanshan Lv , Juntao Wei  and Mingshun Jiang*. Damage localization method for plate-like composite structure based on valid path optimization and search point matching.  Mechanical Systems and Signal Processing, 182, 109562, 2023.