Clément Grisi obtained his MSc in Applied Mathematics & Computer Vision from École des Ponts ParisTech and ENS Paris-Saclay (master MVA - Mathematics, Vision, Learning) in 2021. For his master thesis, he worked on the identification of novel breast cancer biomarkers in digital pathology slides at Paige, in New-York, under the supervision of Pr. Christopher Kanan. As of September 2022, he started as a PhD candidate in the Computational Pathology Group where he works under the supervision of Geert Litjens. His project aims at combining weakly-supervised learning with natural language processing to make predictive models more effective in medical applications and endow them with transparency and explainability.