Yuejian Chen

Dr. Yuejian Chen is an Assistant Professor in the Department of Mechanical Engineering at the University of Manitoba's Price Faculty of Engineering. His research focuses on dynamic modelling, vibration signal processing, artificial intelligence, and prognosis/health management for complex systems like railway vehicles, wind turbines, and steam turbines. He holds a PhD from the University of Alberta (2020) and was a postdoctoral fellow there until 2021. Prior to joining the University of Manitoba in 2024, he served as an Assistant Professor at Tongji University's Institute of Rail Transit in China from 2021 to 2024.

His research integrates digital twins and advanced health management methodologies to ensure safe and cost-effective operation of mechanical systems. Key areas include non-stationary vibration analysis, fault detection via AI (e.g., LSTM networks), and physics-informed machine learning. He has authored/co-authored over 60 publications and serves on editorial boards for journals such as IEEE Sensors Journal, IEEE Transactions on Instrumentation and Measurement, and Smart and Resilient Transportation.

Dr. Chen's work bridges theoretical advancements with practical applications, emphasizing railway transportation and energy systems. His recent publications (2021–2025) highlight contributions to gearbox fault detection under variable speed conditions, multi-camera metro monitoring systems, and data-driven load identification strategies. His research trends emphasize fusion of physical principles with AI for robust diagnostics and health management across mechanical systems.

He is actively recruiting graduate students interested in dynamic systems, signal processing, and AI applications in mechanical engineering. His research group collaborates with industry partners to address real-world challenges in machinery safety and efficiency.