I am Assistant Professor in the Data Intensive Systems group at the Department of Information and Computing Science. My work is in the area of financial fraud detection, in a partnership with ING Bank. The purpose of this work is to expand the state-of-the-art with scalable graph-based methods that exploit the network of financial transactions.

Before joining Utrecht University, I finished my PhD at Digital Enterprise Research Institute (DERI), Galway, Ireland and I was a post-doc at University of Mannheim, Germany. During my studies I focused on the analysis of the graph structure of semantic knowledge bases, to solve NLP problems such as word-sense disambiguation, semantic relatedness computation, and probabilistic topic labelling. After finishing my PhD, I joined the Data and Web Science group at the University of Mannheim, Germany as a post doctoral researcher. In this position, I expanded my research into the area of natural language argumentation investigating several directions such as: the use of external knowledge for explaining arguments, how morality is reflected in argumentation, and stance detection based on expressed good/bad consequences. At the same time, I have been active in financial graph analysis, particularly applied to VC investment graphs like Crunchbase - a research direction that I pursued in the context of an industry funded project, and subsequently in multiple Bachelor and Master thesis that I supervised. At the University of Mannheim, I ran the Network Analysis course within the Master of Business Informatics and Master of Data Science programs.