Applied Scientist & AI/ML Engineer Medical AI · Computer Vision · LLM Systems · Trustworthy AI

I build reliable AI/ML systems for medical, scientific, and regulated domains, from research prototypes to deployable software.

After a PhD and postdoctoral research in computer vision and medical AI, I am focused on bringing robust, useful AI systems into industry.

• Medical AI & computer vision Computational pathology, surgical vision, segmentation, detection, and scene understanding.

• LLM systems & agents Local and cloud-based RAG, multi-agent pipelines, LangChain/LangGraph, LlamaIndex, CrewAI, and MCP-based workflows.

• Trustworthy and regulated AI Practical AI governance, validation, documentation, and lifecycle processes for the EU AI Act, GDPR, and ISO/IEC 42001. TÜV Rheinland certified AI Officer / KI-Beauftragter.

RAG over the EU AI Act: A hands-on tutorial for building a fully local RAG pipeline using Qwen2.5 to answer questions about the EU AI Act. The project covers a simple RAG system design to answer practical AI governance questions. (Slides in German)

AI/ML PyTorch, scikit-learn, MLflow, Weights & Biases, computer vision, medical image analysis, model evaluation

LLMs & agents LangChain, LangGraph, LlamaIndex, CrewAI, RAG, MCP, OpenAI/Codex, Claude

Software engineering Python, C/C++, CUDA, Bash, Git, CI/CD, Docker, REST APIs, clean code, OOP

Data & scientific computing NumPy, pandas, SciPy, OpenCV, scikit-image, PIL, HDF5

Cloud & databases AWS, Azure ML, PostgreSQL, SQL, MongoDB

• Ph.D., Computer Science University of Tübingen, Germany magna cum laude

• B.Sc. / M.Sc., Electronics Engineering

Based in Germany · open to Applied Scientist / AI–ML Engineer roles · EN · DE · TR