Nils Hütten

Nils Hütten is a Scientific Researcher and doctoral student at the Institute for Technologies and Management of Digital Transformation (TMDT) at the University of Wuppertal, where he has been a research assistant since March 2021. His work focuses on industrial applications of artificial intelligence, particularly in computer vision and model interpretability.

His research interests include:

• Machine Learning and Deep Learning
• Computer Vision for industrial inspection
• Explainable AI (XAI)
• AI traceability in production systems
• Predictive maintenance using neural networks

The recent publications by Mr. Hütten demonstrate a consistent focus on applying deep learning models—such as vision transformers and convolutional neural networks—to real-world manufacturing challenges, especially in automated visual inspection and failure prediction. His work emphasizes transparency, interpretability, and practical deployment of AI in industrial settings.

He has contributed to several peer-reviewed publications in applied sciences and engineering journals, reflecting a strong orientation toward solving tangible problems in industry through advanced AI techniques.

Mr. Hütten studied Mechanical Engineering at RWTH Aachen University, specializing in information technology and medical technology. His master's thesis explored the visualization of AI decision-making and improving model traceability in production environments, laying the foundation for his current research.

He is actively involved in research but no scientific awards or student advisement roles are currently documented.

Nils Hütten is based at the University of Wuppertal and works within the Institute for Technologies and Management of Digital Transformation. His research contributes to the broader goals of digital transformation in industrial contexts, particularly through trustworthy and explainable AI systems.