About / working principles
I work where models meet real-world constraints and usable software.
I am a Dresden-based software and applied AI engineer with a German Diplom in Business Informatics from TU Dresden. My work spans machine learning, optimization, RAG and engineer-facing software.
Who I am
My background connects advanced data analytics with software delivery. I am most useful on problems where the model is only one part of a larger system: domain rules, data quality, user decisions and operational boundaries matter just as much.
What I build
I have built industrial signal-analysis tools and ML services, simulation-driven optimization software, constrained reinforcement-learning solvers, and source-grounded knowledge and agent workflows.
How I approach engineering
I start by making constraints explicit. I compare learned approaches with interpretable baselines, keep model outputs behind typed boundaries, and design human review where automation should not silently become truth.
Current interests
My current interests include trustworthy agent workflows, inspectable RAG and knowledge graphs, reinforcement learning for constrained decisions, and the engineering needed to turn experiments into reliable tools.
What I am looking for
I am interested in applied AI, machine-learning and software-engineering roles where technical depth, careful evaluation and product responsibility belong together.
Communication
Languages
- Mandarin · Native
- German · C1
- English · C1