Magnus Munk Jensen

About

I am a PhD fellow working on condition monitoring of main bearings in wind turbines. My research focuses on enhancing machine learning and deep learning methods by incorporating physical insights and model-based knowledge. I also investigate how to integrate data from multiple sensors in controlled environments and apply this knowledge to real-world, noisy settings with limited sensor availability.
I am currently affiliated with Aalborg University.
My research is supported by Innovation Fund Denmark and Siemens Gamesa Renewable Energy.

Research Interests

- Structurual Condition Monitoring
- Physics Enhanced Machine Learning and Deep Learning
- Acoustics

Publications

- Application of pseudo-anomaly generation in unsupervised fault diagnosis of wind turbine bearings under changing operating conditions, International Operational Modal Analysis Conference (IOMAC), 2025

Teaching

- 2025, Teaching Assistant: Digital systems and programming
- 2025, Teaching Assistant: Real time systems and data accousistion

Contact

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AAU VBN
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