Fellow Detail

Green computing Sustainability Radiogenomics Computational biology

I am currently a Research Associate in Biomedical Data Science at the University of Cambridge. I spend half of my time leading the Green Algorithms initiative to promote more environmentally sustainable computational science and the other half thinking of ways to combine machine learning, genomics and medical imaging to better understand cardiovascular diseases.

I first studied in Paris (France) at Lycée Saint-Louis and ENSAE Paris where I earned a BSc and a French Diplôme d’Ingénieur (MSc) majoring in mathematics and statistics, with minors in theoretical physics and economics. I then earned an MSc in statistics and machine learning from the University of Oxford. I joined Cambridge and the Cardiovascular Epidemiology Unit in 2018 for a PhD in Health Data Science supervised by Prof. Michael Inouye and supported by the MRC-DTP. My PhD, completed in 2022, looked at machine learning tools used to predict protein-protein interactions and the carbon footprint of computational research.

As part of the SSI fellowship, I try to raise awareness around the environmental impacts of computational science and continue to help scientists across all fields to quantify and reduce the carbon footprint of their work.