Functional data analysis for computational biology

Marzia develops statistical techniques for the analysis of large, high-dimensional and complex data – in particular functional data. An important aspect of her research is its collaborative and multidisciplinary nature. Indeed, much of her work is at the interface between statistics and computational biology, and her main application area is in the “Omics” sciences.

Kateryna is interested in genomics, evolution, and human genetics. Her lab studies mutations using both computational and experimental approaches. Additional topics of interest include sex chromosome evolution and genomics of childhood obesity.

Matthew’s research interests include functional data analysis, longitudinal data analysis, and data privacy with applications to Omics data.

Francesca is a statistician developing methods for the analysis of large, high-dimensional and complex data, and applying such methods in contemporary “Omics” sciences and other scientific fields – including Meteorology and Economics.