Research software classification
Machine learning and semantic alignment methods for making scientific software easier to categorize, discover, and reuse.
Open related projectResearch
Jenifer is completing a part-time PhD in Artificial Intelligence focused on research software classification, scientific knowledge graphs, semantic alignment, and reproducible research infrastructure.
PhD focus
The research asks how repository metadata, publication text, taxonomies, and scientific knowledge graphs can support scalable and interpretable research software classification.
The practical goal is better discovery and reuse of software that supports computational science, without treating repositories as isolated code artifacts.
Research areas
These topics give search engines and human readers clearer entry points into the research portfolio.
Machine learning and semantic alignment methods for making scientific software easier to categorize, discover, and reuse.
Open related projectComparative analysis of scientific knowledge graph annotations, ontology evolution, and interoperability across research metadata systems.
Open related projectApplied methods for extracting, validating, and retrieving information from unstructured or semi-structured documents.
Open related projectPublications
The full publication index includes abstracts, PDFs or DOI links where available, BibTeX, and related project links.
Conference paper · ISWC 2025 Companion Volume, Nara, Japan
Workshop paper · Sci-K 2025 at ISWC, CEUR Workshop Proceedings 4065
Workshop paper · Natural Scientific Language Processing at ESWC 2025
Conference paper · Companion Proceedings of the ACM Web Conference 2025
Workshop paper · Natural Scientific Language Processing and Research Knowledge Graphs
Related projects
AI · data engineering · applied research
Reach out about roles, consulting conversations, research questions, or technical collaboration in Zurich, Switzerland, or remote teams.