Publication Profile
Scopus
Academic Background 🎓
Prof. Dr. Weidong Jiao holds a strong academic foundation in mechanical and safety engineering. He obtained his B.E. and M.E. degrees from Gansu University of Technology and later earned his Ph.D. in Mechanical Engineering from Zhejiang University in 2004. His educational background aligns well with high-impact research in engineering.
Professional Experience 👨🏫
Prof. Jiao has held faculty positions at Jiaxing University and Zhejiang Normal University. Since 2013, he has served as a Professor at Zhejiang Normal University’s School of Engineering, showcasing his long-term commitment to research and academia.
Research Focus 🔬⚙️
Prof. Dr. Weidong Jiao specializes in mechanical fault diagnosis, signal processing, and intelligent condition monitoring. His work includes bearing fault detection 🛠️, rotor fault diagnosis 🚀, and high-speed train instability analysis 🚆 using deep learning 🤖, wavelet transforms 📊, and graph neural networks. Additionally, he explores brain functional networks 🧠, mental fatigue detection 💤, and EEG-based fatigue analysis for human performance monitoring. His research spans mechanical engineering, artificial intelligence, and neuroscience, contributing to smart diagnostics and industrial safety. As an editor and innovator, he advances predictive maintenance and
Publication Top Notes
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“Novel Imbalanced Multi-Class Fault Diagnosis Method Using Transfer Learning and Oversampling Strategies-Based Multi-Layer Support Vector Machines (ML-SVMs)” (2024)
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“Advances and Challenges in the Hunting Instability Diagnosis of High-Speed Trains” (2024)
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“Efficient Fault Detection of Rotor Minor Inter-Turn Short Circuit in Induction Machines Using Wavelet Transform and Empirical Mode Decomposition” (2023)
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“Driving Fatigue Detection with Three Non-Hair-Bearing EEG Channels and Modified Transformer Model” (2022)
“Reorganization of Brain Functional Network during Task Switching before and after Mental Fatigue” (2022)
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“Multi-Scale Sample Entropy-Based Energy Moment Features Applied to Fault Classification” (2021)
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“A Novel Rolling Bearing Defect Detection Method Based on Bispectrum Analysis and Cloud Model-Improved EEMD” (2020)
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“The Maximum Eigenvalue of the Brain Functional Network Adjacency Matrix: Meaning and Application in Mental Fatigue Evaluation” (2020)
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“Effects of Mental Fatigue on Small-World Brain Functional Network Organization” (2019)
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“A New Method for Automatically Modelling Brain Functional Networks” (2018)
Conclusion 🏆
Prof. Dr. Weidong Jiao is highly suitable for the Best Researcher Award due to his strong academic background, extensive research contributions, numerous publications, patents, and leadership roles in mechanical engineering. His work in smart testing, fault diagnosis, and mechanical dynamics significantly impacts industry and academia, making him a deserving candidate for this recognition.