Research
Current and past research projects
Research Focus
My research focuses on FAIR data principles, machine learning, natural language processing, and data sovereignty. I work on building infrastructure and services for data science research, with particular emphasis on making research data findable, accessible, interoperable, and reusable.
Active Projects
AI-BioDynamics
ActiveTransforming biodiversity monitoring through an AI-driven platform that integrates multi-source environmental data and transfer-learning models to generate actionable insights for conservation and ESG decision-making.
- 2 German Partners and 3 South-Korean Partners
Building a comprehensive research data infrastructure for data science and artificial intelligence in Germany, connecting 17 institutions nationwide.
- 17 German Research Institutions
NFDI4Health
ActiveNational research data infrastructure for personal health data, supporting interdisciplinary health research.
FAIR Data Spaces
ActiveBuilding a common cloud-based data space for industry and science by linking Gaia-X and NFDI initiatives.
Developing AI-powered solutions for monitoring and preserving cultural heritage sites using non-destructive technologies.
Developing multi-agent large language model systems to empower patients with clear and accessible healthcare information.
Developing next-generation data space technologies with AI-enhanced interfaces and cross-sector interoperability.
FDO Connect
ActiveDeveloping infrastructure for FAIR Digital Objects with nanopublication-based systems and automated tools.
RESONANCE: RESpONnsible compliance assistANCE platform
ActivePlatform for deploying fair and privacy-preserving AI in SMEs with responsible compliance assistance.
K-Netz_DTM
ActiveCompetence network for data trustee models in digital ecosystems.
Completed Projects
Developing methods for understanding and analyzing citation patterns in social sciences research literature.
Automated extraction and processing of citations from PDF documents using machine learning techniques.
FATA: False-Alarms in Train Monitoring and their Automatic Discovery
CompletedDeveloping AI-based systems to automatically detect and reduce false alarms in train monitoring systems.
Developing privacy-preserving AI solutions for healthcare document processing in European healthcare systems.
Research Areas
FAIR Data
Research data management, FAIR principles implementation, data spaces
Machine Learning
Deep learning, neural networks, computer vision, pattern recognition
NLP
Text mining, author name disambiguation, metadata extraction
Data Sovereignty
Data governance, privacy-preserving technologies, Gaia-X
Knowledge Graphs
Research knowledge graphs, semantic data integration, FAIR Digital Objects
Information Retrieval
Web search, digital libraries, scholarly data mining