Junior Research Group Medical Image Computing

Welcome

I am a researcher working at the intersection of machine learning and medical image analysis, with a particular focus on uncertainty-aware and knowledge-informed approaches. My work aims to make deep learning models more reliable, interpretable, and robust for real-world applications.

I am leading the Junior Research Group Medical Image Computing within the Chair of Marine Data Science, headed by Jun.-Prof. Stefan Lüdtke, at the University of Rostock.

Research Interests

My current research focuses on:

• Uncertainty-Aware Image Processing
  Developing models that can quantify and communicate their uncertainty, including approaches from probabilistic machine learning and evidential deep learning.

• Knowledge-Informed Deep Learning
  Integrating prior knowledge, physical constraints, or domain expertise into deep learning models to improve generalization and trustworthiness.

Applications

I apply these methods primarily in the field of medical imaging, including:

• Angiography
• X-ray
• 2D / 3D Ultrasound imaging
• Other clinical imaging modalities

The goal is to build systems that are not only accurate, but also reliable and clinically meaningful.

Vision

Modern machine learning systems are increasingly used in high-stakes domains such as healthcare.
My research aims to bridge the gap between state-of-the-art AI methods and trustworthy deployment in practice, by making models:

• More transparent
• More robust
• More aware of their limitations

Contact

Feel free to reach out if you are interested in collaboration or have questions about my work.