Classification and cluster analysis:Development and application of statistical methods for supervised and unsupervised classification, with a focus on model-based clustering, high-dimensional data, categorical data, textual data, functional data and imbalanced classification problems.
Multivariate analysis: Statistical analysis of multivariate data, with attention to dependence structures, dimensionality reduction, covariance modelling, and the synthesis of complex information from multiple variables. Artificial data generation.
Statistics in medicine: application of statistical methods to biomedical and clinical research, including the analysis of observational, experimental, and high-dimensional data to support diagnosis, prognosis, and treatment evaluation.
