I am a researcher in Knowledge Representation, Logics and Databases. My main interest are KR for data quality and efficient algorithms for logical reasoning, however I am interested in all topics related to applied KR and KG construction, including mapping languages for KGs, entity linking and disambiguation, machine learning for relation extraction and validation, information extraction for KG construction and more recently, graph embeddings and text embeddings for non-logical inference over graphs.
I worked in IBM AI where I served as technology lead in projects focused on knowledge management, integration and reasoning. I currently work in Google NYC as an Ontologist/Linguist in the KG Schema team.
The topic of my Ph.D. dissertation was efficient query-rewriting-based reasoning techniques for OWL2 QL and SPARQL. I lead a team in the development of -ontop-, a system for on-the-fly SPARQL to SQL that implements the ideas behind my dissertation (e.g., OWL2QL/RDFS reasoning on virtual R2RML graphs, efficient query rewriting through pre-compiled inferences in R2RML mappings, and query rewriting optimization through semantic query optimization).