Local knowledge systems
Privacy-conscious assistants that retrieve evidence from an organization’s own documents and make sources visible.
Explore local RAG →I develop and evaluate local AI systems for research, higher education and knowledge-intensive applications — with a focus on Retrieval-Augmented Generation, task-specific fine-tuning, reproducibility and measurable quality.
From document collections and retrieval pipelines to specialized language models and transparent evaluation.
Privacy-conscious assistants that retrieve evidence from an organization’s own documents and make sources visible.
Explore local RAG →Improving small and medium open-weight language models for grounded answers, hard negatives and structured output.
Explore TSFT-RAG →Comparing base and tuned models with realistic test sets, citation checks and reproducible metrics.
Explore evaluation →Public model releases, repositories and technical documentation make experiments inspectable and reusable.
Applied research connecting technical development, university practice and open knowledge.
Local AI-supported FAQ systems for teaching, student services and university administration.
Project details →An experimental memory and retrieval assistant that connects conversational interaction with controlled document retrieval.
Project details →More than two decades of courses, examples, package documentation and material for scientific writing.
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