Wilhelm Wermelin
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Email
Location
Mölndal
ORCID
Research Interests
Wilhelm has a background in physics and applied mathematics. His research interests include data analysis, machine learning and data management in industry and production. The research involves applying data driven methods in an industrial context such as e.g.
- Smart and data-driven maintenance
- Quality control
- Disturbance handling
- Traceability
An important aspect in the research is to explore how small and medium sized enterprises (SME's) can adopt new digital technologies and methods for strengthening their competitiveness.
Projects
Wilhelm has worked in projects regarding digitalization of induction hardening (DigPIn), data-driven disturbance handling (D3H) and increased reliability in electronic components (iREL4.0).
He is also a PhD student in the research school IndTech at Mälardalens University where research is focused on resource optimization and analysis of energy systems.
Keywords: data, deep learning, computer vision, predictive maintenance, artificial intelligence, optimization, mathematical modeling, Python, NumPy, Pandas, PyTorch, JAXAsk me about
Publications
Ask me about
Publications
- Differentially Private Federated Learning for Remaining Useful Life Prediction
- Challenges and Future Directions in Federated Learning for RUL Estimation in Po…
- Comparing Feature and Trajectory-Based Remaining Useful Life Modeling of Electr…
- Collaborative Training of Data-Driven Remaining Useful Life Prediction Models U…
- A Link between the Lab and the Real World-A Setup for Accelerated Aging of Powe…
- Simple Hybrid Model for Estimating Remaining Useful Life of SiC MOSFETs in Powe…
- Data-Driven Remaining Useful Life Estimation of Discrete Power Electronic Devic…