About
I'm a Machine Learning Engineer at ITSC GmbH, working in the health insurance sector. I'm passionate about integrating ML models into traditional workflows — supporting and enhancing the work people already do, not replacing it. My goal is to help people live longer, healthier lives by bringing data-driven insights into the processes that matter. I'm particularly interested in RAG-based architectures and scalable ML pipelines.
Education
Ph.D. in Theoretical Computer Science
Paderborn University
My academic background in theoretical computer science gives me a strong foundation for tackling complex, abstract problems and designing rigorous, well-reasoned solutions. This ability to think formally and break down hard problems carries directly into my engineering work — whether it's optimizing ML pipelines, designing scalable architectures, or reasoning about algorithmic trade-offs in production systems.
Dissertation: Local Protocols for Contracting and Expanding Robot Formation Problems
Tech Stack
ML & Deep Learning
Data Engineering
MLOps & Infrastructure
Visualization
Interests
Production ML
Building robust, scalable pipelines that take models from experimentation to production. Focused on reproducibility, monitoring, and continuous training workflows.
RAG Architectures
Exploring retrieval-augmented generation systems that combine the strengths of large language models with structured knowledge retrieval for more accurate, grounded outputs.