My main research interest is structured machine learning and its application on Big Data problems. As part of the MOLE group I am contributing to the DL-Learner framework trying to adapt and extend it for bigger life science use-cases. Besides this, further efforts concern the parallelization of existing learning algorithms on shared memory and shared nothing architectures.
- DL-Learner – a tool for supervised Machine Learning in OWL and Description Logics
- GeoKnow – Making the Web an Exploratory for Geospatial Knowledge
- LinkedGeoData – adds a spatial dimension to the Web of Data
- RDFUnit – an RDF Unit-Testing suite
- SANSA-Stack – Open source platform for distributed data processing for RDF large-scale datasets
- SML-Bench – A Benchmark for Symbolic Supervised Machine Learning from Expressive Structured Data
- Sparqlify – a SPARQL-SQL rewriter