Joined department in 2006

Professor Neville's research focuses on data mining and machine learning techniques for relational data. In relational domains such as bioinformatics, citation analysis, epidemiology, fraud detection, and web analytics, there is often limited information about any one entity in isolation, instead it is the connections among entities that are of crucial importance to pattern discovery. Relational data mining techniques move beyond the conventional analysis of entities in isolation to analyze networks of interconnected entities, exploiting the connections among entities to improve both descriptive and predictive models. Professor Neville's research interests lie in the development and analysis of relational learning algorithms and the application of those algorithms to real-world tasks.