I am a Scientific Lead in the Marks lab at Harvard Medical school, where I lead the subgroup focusing on protein engineering. My research lies at the intersection of Generative AI, Computational Biology and Chemistry. I am passionate about the use of Machine Learning models to design novel biomolecules to address challenges in healthcare and sustainability.

I completed my PhD in the Oxford Applied and Theoretical Machine Learning Group, under the supervision of Yarin Gal. During my time there, I developed large-scale protein language models for fitness prediction and design (Tranception, TranceptEVE, RITA, ProteinNPT), as well as deep generative models to predict the impact of genetic mutations in humans (EVE) or to identify viral mutations likely to escape immunity (EVEscape). With colleagues from the Marks lab, I also lead the development of the ProteinGym benchmarks, which many have found to be a useful resource to evaluate protein models.

Before returning to academia, I was a Senior Engagement Manager at McKinsey & Company where I developed an expertise in Digital & Analytics strategy, and lead cross-disciplinary teams on high-impact analytics projects, primarily in the healthcare and pharmaceutical sectors. I obtained an M.S. in Operations Research from Columbia University, and a B.S. & M.S. in Applied Mathematics and Physics from Ecole Polytechnique.