About

Computer vision @Owkin

I am currently working as a data scientist at Owkin. Owkin is an emerging biotech company with the mission to find the right treatment for every patient. At Owkin, we are leveraging cutting-edge machine learning to deliver better drugs and diagnostics at scale. I am part of the Medical Imaging group, focusing on the analysis and representation of histopathology data. More specically, my missions involve improving our histology-based, AI-guided diagnostics tools such as RlapsRisk BC; which can be done through complex model understanding and data representation. Among others, I have been working within R&D on self-supervised learning to better represent digital pathology data, that ultimately fuel all our pathology AI solutions and empower pathologists and researchers with increasingly accurate AI assistants for the benefits of patients.

Past experience in computer vision and medical research

After graduading, I spent two years in the Include team, the data wharehouse of Lille University Hospital created in 2018 and authorized by the CNIL to reuse patients’ data for clinical and methodological research. I gained expertise in (bio)statistics and machine learning techniques (e.g. clustering, survival analysis, time series analysis) through diverse collaborations with researchers and phyicians. In the mean time, I started to specialize in computational pathology through a 2-year collaboration with Dr. Florence Renaud, pathologist, on the prediction of molecular subtypes in esogastric adenocarcinomas. Then, I joined the ENDOMIC (Inserm | INRIA) team as a data scientist. Here, I continued working on computational pathology but also on the analysis of immunofluorescence images through a 1-year collaboration with the immunology institute of Lille University Hospital (Pr. Sylvain Dubucquoi, Pr. Vincent Sobanski).