My research focuses on developing statistical methods applied to women’s health and menstrual health in particular. This includes research on fertility, on cycle-related symptoms and on drivers of changes in vaginal microbiota communities. I address my research questions by creating parametric and nonparametric statistical models of biological processes that I fit to multi-domain clinical data, self-reported digital records (data from mobile phone apps), and publicly available datasets.
I obtained my PhD in computational biology from the École Polytechnique Fédérale de Lausanne (EPFL), in Switzerland, where I worked on the molecular regulation of the circadian clock. In particular I was interested in the regulation of rhythmic gene expression and protein translation combining analyses of -omics data with mathematical models describing the regulatory dynamics to infer quantities otherwise not measurable.
I have also specialized in the visualization of data and, during my industry experience, have helped companies and organizations to take data-driven decisions.