About

Currently at BMW Group, I build AI systems that turn large volumes of engineering documentation into a living knowledge graph for compliance verification and cross-document reasoning. Before BMW, I worked as the head of AI solutions at Qubicon as an AI & Software Engineer, building Python SDKs and AI-driven tools that are now actively used across the bioprocessing sector. Earlier, I co-authored a Springer-published research paper at the intersection of AI and geospatial systems while still in my first year of university.

I hold a B.Sc. in Artificial Intelligence from TH Deggendorf, one of the first universities globally to offer the degree. My work spans the full stack, from ML model design and LLM workflows to production deployment, system architecture, automation, and interfaces people can actually use. I focus on building systems that survive contact with reality.

I treat everything I build as part of a larger foundation. I am not interested in what is merely trendy. I am interested in what is hard, what is real, and what compounds.

I believe that technology should augment human capabilities rather than replace them. My approach to innovation is guided by three core principles:

1. Human-Centered Design: Technology must be designed with a deep understanding of human needs, behaviors, and contexts. The most powerful innovations are those that seamlessly integrate into people's lives and enhance their capabilities.
2. Ethical Innovation: As we develop increasingly powerful technologies, we must consider their ethical implications and potential societal impacts. I am committed to creating technologies that promote equity, transparency, and human flourishing.
3. Cross-Disciplinary Collaboration: The most significant breakthroughs occur at the intersection of different fields. By bringing together diverse perspectives and expertise, we can develop more comprehensive and effective solutions to complex problems.