Wilhelm Söderkvist Vermelin

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, JAX