I design and build AI-driven decision systems for complex operational environments.
With a doctoral degree in technical mathematics (TU Graz, graduated sub auspiciis Praesidentis) and training in AI strategy (MIT Sloan) and AI governance (Oxford Saïd Business School), I work at the intersection of machine learning, optimisation, and trustworthy AI.
At Anexia, I focus on turning models into production-grade solutions that automate and improve high-impact operational decisions – not just prototypes, but systems that create measurable business value. Additionally, I teach mathematics at the University of Klagenfurt, bridging theory and practice.
AI-driven decision systems and optimisation · Explainable and trustworthy AI · AI governance and responsible deployment · ML and GenAI in operational contexts
Discrete mathematics and combinatorics · Applied optimisation (mixed-integer, linear) · Algorithmic thinking and formal modelling
Saïd Business School, University of Oxford
2025
AI governance, EU AI Act, regulatory frameworks, and responsible AI.
MIT Sloan School of Management
2025
AI strategy, organisational implementation, and business impact.
Federal President of Austria
2024
Highest academic honour in Austria, conferred by the Federal President.
Austrian Federal Ministry
2020
National award for outstanding master's thesis.
AI coding agents are rapidly becoming part of the developer stack. But while the ecosystem moves fast, one question is becoming critical in regulated environments: who actually controls what these agents do at runtime?
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One of the most impactful talks I attended at Codemotion Milano 2025 showed how semantic routing, vector similarity search and semantic caching can dramatically reduce token usage, latency and energy consumption, while keeping quality and context intact.
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In July, I had the wonderful opportunity to attend the RAISE Summit 2025 in Paris together with my colleague Harald Nezbeda, thanks to the generous support of Anexia. The event took place at the Carro
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