I graduated with a BSc in Mathematics from the Aristotle University of Thessaloniki, Greece in 2003 and I received an MSc in Applied Statistics from the University of Piraeus in 2006. From 2006 till 2011, I studied for my Ph.D. in Statistics at the University of Florida, USA.

Upon completion of my doctoral studies in August 2011, I returned to Europe where I worked for two years as a joint postdoc fellow at the European Bioinformatics Institute and the University of Cambridge. I continued working as a Research Associate at the Statistics and Computational Biology group at the University of Cambridge for another two years before moving to the University of Brighton in 2015.

Broadly speaking, my research interests and activity falls within the areas of biostatistics, categorical data analysis, high-dimensional statistics, and statistical genetics focusing on statistical methods for multivariate or high-dimensional data. In particular, I am interested in developing regression techniques for correlated responses, estimation methods of large covariance matrices, and hypothesis testing procedures in high-dimensional settings. Although my research is motivated by cross-disciplinary collaborations with biologists, bioinformaticians, computer scientists, and doctors, it finds application in a wide range of studies, including studies in social sciences, health studies, and omics-studies among others. I disseminate the developed methods in R packages that are contributed to the R-CRAN and Bioconductor projects.

I have taught a variety of undergraduate and postgraduate statistical modules at the University of Brighton, including both specialised and non-specialised audiences. I insist more on the understanding of statistical concepts rather than on the memorisation of technical details and thus encouraging independent critical thinking. I also include contemporary statistical software, such as R and SAS, in my teaching material to help students develop soft skills that tend to be helpful in their future careers.

I am interested in supervising postgraduate research students in machine learning methods, categorical data analysis, multivariate analysis and high-dimensional statistics. Projects are likely to involve development of open-source software to support and disseminate the findings of the research.