| Data Science and AI – Machine Learning |
I am mostly interested in Knowledge Discovery in Databases, Data Mining and Statistical Computing. My main research is focusing on applying Machine Learning and Statistical Learning methods to genotype, phenotype and clinical data in-order to discover patterns of interest, including the identification of clinical and genetic predictors with respect to diseases.
My current research is in the broader areas of Data Science and AI – Machine Learning. In particular I am interested in Machine Learning, Statistical Learning, and Predictive Modelling with a particular focus on: (a) Predictive modeling & computational psychiatry – in collaboration with Institute of Psychiatry, Psychology and Neuroscience at King’s College London and Department of Computing at Goldsmiths, University of London; (b) Predicting risk of dementia using routine primary care records, work in collaboration with University of Manchester and other partner universities; (d) Decision trees and ensemble based methods with parameterized impurity families and statistical pruning (e) Mobility big data analytics – focusing on using the experience sampling method with mobile applications in order to predict a class. Another component of my research focuses on data uncertainty approaches, symmetry detection approaches and database administration approaches. |