Developing efficient algorithms for clustering and/or classification of large and complex data (DELAIGLESIAU16SF)

Dr. de la Iglesia’s main research interests are in developing data mining algorithms and in their application to areas such as medical data and financial data. Past projects have included Privacy Preserving Data Mining, clustering and classification using optimisation techniques, creation, simplification and presentation of rule sets, text mining and preparation and analysis of health data. Current projects include extraction of data from multiple Hospital Information Systems to create clinical pathways and the analysis of complex data using clustering algorithms. She would welcome applications from students who have secured their own funding and who wish to work in any areas of data mining algorithm development in line with her previous research or on applications of data mining that are not standard and present some research challenges. Dr. de la Iglesia is willing to discuss specific PhD project proposals that fall within that remit and may have some readily available projects in the analysis of previously collected health data.