Junyu Qi

Dr.-Ing. Junyu Qi serves as a Scientific Researcher at the Reutlingen Research Institute within the Faculty of Technology at Reutlingen University, Germany. His primary affiliation is with the Drive Technology research group under the Electronics & Drives division, where he conducts advanced research in condition monitoring and predictive maintenance for industrial machinery.

• Education: B.Sc. in Mechatronics from Shanghai Maritime University (2008-2012), M.Sc. in Mechatronics from Friedrich-Alexander-Universität Erlangen-Nürnberg (2013-2016)
• Professional Experience: Researcher at KU Leuven's Department of Mechanical Engineering (2017-2023), Bosch Rexroth engineer (2015-2016)

Qi's research centers on AI-driven predictive maintenance systems, specializing in vibration analysis and cyclostationary signal processing for rotating machinery. His work bridges statistical modeling with deep learning to develop robust diagnostic frameworks for wind turbine drivetrains, roller chain systems, and planetary gearboxes. Key innovations include sensorless monitoring techniques using motor current data and multi-sensor fusion architectures for remaining useful life prediction.

His publication portfolio shows a clear trajectory toward integrating physics-informed AI with industrial applications, with recent work emphasizing few-shot learning for data-scarce scenarios and federated learning for distributed industrial systems. Over 70% of his publications focus on wind turbine diagnostics and bearing prognostics.

• Best Paper Award, American Society of Mechanical Engineers (ASME) 2020 for wind turbine gearbox research
• Regular reviewer for Mechanical Systems and Signal Processing, Reliability Engineering and System Safety, IEEE/ASME Transactions on Mechatronics

Qi actively contributes to the academic community through peer review and conference participation, with no formal teaching responsibilities documented. His current research leverages the Reutlingen University's specialized laboratories for drive technology and vibration analysis to develop deployable industrial solutions.