I am currently a Research Associate in Biomedical Data Science at the University of Cambridge.

I was initially trained in Paris (France) at Lycée Saint-Louis (2013-15) and ENSAE Paris (2015-17), where I earned a BSc and a French Diplôme d’ingénieur (MSc) studying mainly mathematics and statistics, but also theoretical physics and economics. During these years, I interned as a Data Scientist at Sidetrade (Paris) and Amazon EU (Luxembourg).

In 2017, I headed to the University of Oxford, where I completed an MSc in Statistics and Machine Learning (with Distinction). My Master’s thesis focused on developing a Bayesian tree-based algorithm to predict the length of hospital stays for patients, working with Prof. Mihaela van der Schaar.

I joined the Inouye Lab and the University of Cambridge in 2018 for a PhD in Health Data Science supervised by Prof. Mike Inouye. Between 2018 and 2022, I worked on protein-protein interaction prediction but also how to make computational research more sustainable.

In April 2022, I started as a Research Associate in Biomedical Data Science in the Department of Public Health and Primary Care, still working with Mike Inouye. Go here for more details about my past and current research interests.

I supervise a number of undergraduate students at the University of Cambridge (go here for the full list of courses) and I’m an Associate Fellow of the Higher Education Academy.

For my PhD, I was supported by the MRC Doctoral Training Program through the Industrial Strategy PhD studentship in Data Science and Artificial Intelligence, and HDR-UK. At the University of Cambridge, I’m based in the BHF Cardiovascular Epidemiology Unit and the Cambridge Baker Systems Genomics Initiative in the Department of Public Health and Primary Care (School of Clinical Medicine). I am also a member of Clare Hall College.

Outside of work, I’m involved with the Cambridge University Modern Pentathlon Club (and previously with OUMPA). I also enjoy photography, tennis…