Nicolas Sebastian Schuler
PhD student at Karlsruhe Institute of Technology (KIT)
I study how software systems can adapt to changing conditions while remaining dependable. My research explores how learned models, explicit rules, and evidence from running systems can support better decisions.
Research questions
Software needs to respond when its environment changes or something goes wrong. I explore how to make those responses useful, understandable, and open to checks:
- How can learned models and explicit rules work together so that a system can adapt while respecting its requirements?
- Which details of a software failure help a language model find a fix, and how can we control what information it receives?
- How can we assess and combine explanations from models trained on data held by different participants?
My selected papers explain these questions through concrete projects. For thesis and project enquiries, see teaching and supervision.
News
- Best Paper Award at the ECSA 2026 Doctoral Symposium (Bolzano) for “Architecting Self-Adaptive Systems with Learned and Symbolic Components”
- TraceGate tool paper accepted at ASE 2026 Tools and Datasets
- TraceGate accepted at the ISSRE 2026 Research Track
- Preprint: Metric-Guided Attribution Fusion in Explainable Federated Learning (submitted to Information Fusion)
- “Bridging Explanations and Logics” accepted at AISoLA 2025
Away from research
Outside of work, I’m learning 🇯🇵 Japanese and enjoy riding my 🏍️ motorcycle. Coffee and pizza are usually welcome, too.
If you’d like to talk about research, software, or a shared interest, get in touch.
Best regards,
Nicolas