معرفی
Shuai Zhao is an Assistant Professor at the AAU Energy Department, Faculty of Engineering and Science, Aalborg University. His research focuses on applying machine learning and artificial intelligence techniques to enhance reliability and condition monitoring in power electronic systems, with specific interests in lifetime estimation, fault diagnosis, and health management of critical components like capacitors and semiconductor devices.
- Institution: Aalborg University
- School: Faculty of Engineering and Science
- Department: AAU Energy
- Email: szh@energy.aau.dk
His research spans multiple domains including:
- Physics-informed machine learning for power converter systems
- Remaining useful life prediction with hybrid Bayesian deep learning
- Thermal transient analysis and stress emulation methods
- IoT-enabled monitoring schemes for semiconductor devices
- Neural network applications in lithium-ion battery prognostics
Recent publications show a strong trend toward integrating domain-specific physics with machine learning frameworks to address real-world challenges in:
- Power electronics reliability under operational stress
- Anomaly detection in multivariate time-series data
- Robust fault diagnosis for railway traction systems
- Temperature estimation in electric vehicle motors
- Imbalanced data handling in diagnostic systems
- Capacitance degradation modeling under environmental factors
Current projects demonstrate collaboration with leading institutions on:
- AI-assisted long-term maintenance strategies
- Physics-informed neural network architectures
- Smart agricultural monitoring systems via IoT platforms
- Advanced particle filter methods for life prediction
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