I am currently a PhD candidate in computer vision at the University of Paris-Saclay. My research interests are in computer vision applied to the social sciences. At the moment, I am working on a visual search engine for French sign language at Limsi, as well as a side-project in remote sensing and economics. I also love teaching mathematics/statistics/econometrics-related classes.

After finishing a four-year degree in pure mathematics and a masters degree in economics, I spent 2 incredible years working for eXplain designing targeting and predictive models for major European election campaigns. I recently completed the MVA program at the ENS Paris-Saclay.


Research internship: Automatic alignment of subtitles with French sign language. Supervised by Annelies Braffort and Michèle Gouiffès.

Masters thesis: Optimal Design of Peer Effects Experiments with Exogenous Group Selection. Supervised by Philipp Ketz.

Honours thesis: The Rank of Elliptic Curves over Function Fields of Finite Fields. Supervised by James Borger.


Semester 2 2019/2020: Machine learning in economics (University of Kassel)

Semester 2 2018/2019, 2019/2020: Machine learning in economics (Paris School of Economics) - with Philipp Ketz

Semester 2 2018/2019: Machine learning in economics (University of Hanover)

Semester 1 2018/2019, 2019/2020: Introduction to R (Paris School of Economics) - with Pauline Charousset

Summer 2018: Introduction to Machine Learning using the R package SuperLearner (Summer School organised by Colombia University)

Semester 1 2016/2017, 2017/2018, 2018/2019: Advanced Econometrics with Stata (SciencesPo Paris)

2015/2016: Mathematics and Statistics Tutorials (Paris 2 - Panthéon-Assas)

Semester 1 2014: Mathematics tutorials (Australian National University)


The classes I took under the MVA program are: Deep learning (3 courses), Object recognition and computer vision, Deformable models and geodesic methods for image analysis, Advanced methods for text and graph data, Algorithms for speech and natural language processing, Topological data analysis, Introduction to medical imagery, Remote sensing data, Audio signal analysis, Reinforcement learning, Convex analysis, Probablistic graphical models, Kernel methods for machine learning, Theoretical foundations of deep learning.


Some of my paintings can be found here.