Magnus Munk Jensen

PhD Student · Electronic Systems · Aalborg University

Aalborg, Denmark · magnusmj@es.aau.dk · LinkedIn: magnus-munk-jensen
Magnus Munk Jensen

About

I am a PhD student working with condition monitoring of mechanical systems, with a particular focus on wind turbine main bearings. My research aims to enhance machine learning and deep learning methods by incorporating physical insights and model-based knowledge, enabling robust and interpretable diagnostics in complex and noisy environments.

Research Interests
Signal Processing
Acoustics
Condition Monitoring
Physics-Enhanced Machine Learning
Deep Learning for Mechanical Systems
Hybrid Model-Based & Data-Driven Diagnostics

Background

Aalborg University
Ph.D. Fellow
Denmark
Feb. 2025 – present
  • Project: BeWind (Grand Solutions, Innovation Fund Denmark)
  • Supervisors: Prof. Rafal Wisniewski, Prof. Dorte Hammershøi
  • Industry partner: Siemens Gamesa Renewable Energy
  • Visitng PhD at Intelligent Maintenance and Operations Systems (IMOS) lab, at École Polytechnique Fédérale de Lausanne (EPFL)
    • Host professor: Olga Fink
    • Received travel grant from Knud Højgaards Fond
    • Received travel grant from Otto Mønsteds Fond
Aalborg University
M.Sc. in Electronic Systems
Denmark
2022 – 2024
  • Thesis on diffusion-based speech enhancement
  • Collaboration with GN Store Nord
  • Presented at Audio Analysis Workshop 2024
Aalborg University
B.Eng. in Electronics
Denmark
2017 – 2021
  • Bachelor thesis in collaboration with Deif A/S
Hans Jensen Lubricator
Machine Learning & Electronics R&D Engineer
2021 – 2025

Publications

  • GMM-based subspace fault detection in LPV systems under partially unknown scheduling
    M. M. Jensen, S. Gres, R. Wisniewski, H. Schiøler, D. Hammershøi
    23rd IFAC World Congress, 2026
    Conference paper
  • Application of pseudo-anomaly generation in unsupervised fault diagnosis of wind turbine bearings under changing operating conditions
    M. M. Jensen, S. Gres, R. Wisniewski, D. Hammershøi
    11th International Operational Modal Analysis Conference (IOMAC), 2025
    Conference paper

Academic Service

  • Teaching Assistant: Digital Systems and Programming (Fall 2025)
  • Teaching Assistant: Real-Time Systems and Data Acquisition (Spring 2025)
  • Undergraduate project supervision (Fall 2025)
  • Pedagogical training in Problem-Based Learning (AAU)
  • Participant: Audio Analysis Workshop & Self-Supervised Learning Workshop

Contact

magnusmj@es.aau.dk
AAU VBN
LinkedIn
Contact
Email: magnusmj@es.aau.dk
AAU VBN: vbn.aau.dk/da/persons/magnusmj
LinkedIn: linkedin.com/in/magnus-munk-jensen