French, 22 years old
Research intern in Reinforcement Learing at Laboratoire Cedric (CNAM).
Ecole Polytechnique, Paris (Palaiseau) Master Data Science (applied mathematics department).
- Relevant courses : Optimization, Statistical learning theory, Deep learning and Generative models, High dimensional statistics, Stochastic approximation and Reinforcement learning, Bootstrap and resampling methods, Computer vision.
Télécom Paris, Paris (Palaiseau) Graduate engineering school, majoring in computer science and applied mathematics. (GPA 3.93/4.00)
- Relevant courses : Statistics, Optimization theory, Linear models, Non-Parametric Estimation, Machine learning, NLP, Graph mining.
2016 - 2018
Lycée Jean-Baptiste Say, Paris Classes préparatoires
Lycée Albert Camus, Fréjus Baccalaureate with highest honours
Research Intern in the computer science department of Conservatoire National des Arts et Metiers (CNAM). We try to generate and quantify diversity among reinforcement learning agents. We focus on the notion of perceptual diversity and we link it to the experience of a video game player. Keywords : Deep Reinforcement Learning, Intrinsic Motivation, Quality-Diversity, Skill discovery.
Co-author of the book Intégrer l’X ou l’école d’ingénieurs de tes rêves avec les Sherpas, published in June 2020 by Vuibert (Albin-Michel). The book is a guide for undergraduate students to suceed at the nationwide competitive exams for engineering schools.
Developer of a project on pretraining parameters of a Deep Neural Network using a Deep Belief Network. Implementation from scratch in Python of the DBN structure and CD-1 algorithm. Comparison of the performance between the randomly initialized and the pretrained network on the MNIST dataset.
Winner of the internal Data Challenge of the Msc on Magnetoencephalography (MEG) source localization. The solution used a custom implementation of adaptive Lasso for sparse support recovery and a meta-algorithm for fine-tuning the parameters.
Finalist of the 2021 Huawei Challenge on transfer learning for detecting failures of optical networks. Time series analysis and domain adaptation using both standard statistical tools and deep learning methods.
Competitor in the 2021 edition of Hackaton Hi!Paris (Organized by Ecole Polytechnique and HEC Paris). Optimization of the energy consumption of a building with solar panels using a smart grid controller. We leveraged reinforcement learning methods as well as heuristics to minimize the cost and the environemental impact of our building.
Maintainer of an experiment on predicting outcomes of competitive Counter-Strike games, including a theoretical approach (probabilistic and gambling theory), an implementation using different elo-based computed features as well as simulations to validate winning strategies.
Vice-President of the students sports office an association with 400 contributors, 13 members and more than 80 k€ of budget.
- Management of the whole sport life of the school (infrastructures, coachs, equipments).
President of the cheese club Téléfrom
- Events around cheese, local cheese tasting, raclette, fondue.
- Gathering of hundreds of students within the school.
Skills & Interests
Programming languages: Python (pandas, sklearn, pytorch, gym). A bit of Java, C++, C, JS. Tools: Git, Jupyter. Languages : French native speaker, working profiency in English (C1).