I’m a research scientist dedicated to redefining menstrual health assessment by leveraging the potential of self-tracked data from mobile applications.
The diversity of symptoms tracked and, most importantly, the amount of data that has been collected by millions of users has the potential to aid the assessment of menstrual health and to facilitate the early detection of hormonal imbalances, menstrual disorders or diseases.
My work focuses on the analysis of these data to establish menstrual health indicators.
After my PhD in computational biology studying the molecular regulation of the circadian clock, I worked in the industry for a few years before coming back to academia. In brief, I worked as a data science and data visualisation consultant, in an international organisation focusing on science communication and experience design and as a freelance scientific illustrator. In this context, I have given over 30 workshops in universities and R&D departments.