I am interested in knowledge representation, semantic technologies, graph data mining, machine learning on graphs, and natural language processing.
Especially, I am interested in approaches that combine unstructured data (e.g., text) with structured data (e.g., knowledge graphs), and in machine learning approaches that can exploit background knowledge.
My vision is to develop neuro-semantic approaches that combine logic, statistics, and machine learning to address problems in natural language processing and beyond.
I have carried out research in the areas of machine learning on graphs, link prediction, in-context learning, natural language processing/generation, relation extraction, question answering, information extraction, ontology engineering, explainable AI, graph data mining, and pattern mining.