Biography

I am a physicist interested in computer science and postdoc researcher at the Mathematics and modeling laboratory of Évry (LaMME). I have the background and education of a physicist and did a PhD in optical microscopy (super-resolution with random illumination patterns). I am interested in computer science and did a MS in computer science at CNAM (Conservatoire National des Arts et Metiers, Paris) during my PhD.

In 2018 I joined Médecins Sans Frontieres in the effort of fighting antimicrobial resistances, by starting from scratch the first smartphone-based automatic system for reading disk-diffusion antibiograms. The prototype developed in one year won the Google AI Impact Challenge 2019.

My PhD project was at the same time an experimental and theoretical challenge. It involved the whole design of a new microscope (hardware and driving software), modelling complex light structures and the design of advanced image processing algorithms. If I had to summarize the adventure in a sentence I would say that “during my PhD I developed a novel microscopy technique based on randomly interfering light (apparent disorder) which allows, under certain sparsity constraints, the reconstruction a 3D object from a bi-dimensional image”. I found this idea of retrieving information from partial and chaotic data very exciting.

I like working in interdisciplinary environments where I can bring and make value of my diverse experiences and interests in a team with a wide spectrum of activities and different axes of research. During my experiences in both fields of physics and computer science, I enjoined the rigorous frameworks of mathematical modelling and abstract reasoning.

Undoubtedly, most of my experiences are in image processing and scientific computing. Nevertheless I have interests in statistics and in the practical and formal aspects of software development (e.g. algorithms, languages, abstract syntax trees, proof…)

• ²⁰¹⁷⁄₂₀₁₈ - Introduction to probability
• ²⁰¹⁸⁄₂₀₁₉ - Introduction to the R language
• ²⁰¹⁸⁄₂₀₁₉ - Statistics