Education & Projects
My academic background has provided me with practical skills for high-efficiency coding alongside deep theoretical knowledge in areas like Linear Algebra, Complexity Theory, and Database Theory. All courses were completed with the highest distinction (mention très bien).
My full Curriculum Vitae is available for download here.
Coursework
Artificial Intelligence Courses
- Learning Theory From First Principles (IASD, Francis BACH)
- Computer Vision (Jean Ponce)
- Reinforcement Learning (IASD, Olivier CAPPÉ)
- Convex Optimisation (Adrien Taylor)
- Optimization for machine learning (IASD, Clément W. ROYER)
- Large Language Models (IASD, Alexandre ALLAUZEN)
- LLM for Code and Proof (MVA, Marc LELARGE & Nathanaël Fijalkow)
- Deep Learning For Image Analysis (IASD, Étienne DECENCIÈRE)
- Statistical Learning (Alessandro Rudi)
- Geometric Data Analysis (MVA, Jean Feydy)
- Deep Learning (Kevin Scaman)
- AI Safety Atlas (CesIA)
Data & Database Research
- Research project at NTU Singapore. Supervised by CONG Gao and SHI Jachen.
- Data Acquisition, Extraction, and Storage (IASD, Pierre SENELLART)
- Database Theory (Pierre Senellart)
- Research Internship at INRIA. Supervised by Nofar Carmeli and David Carral
- Supervised research project at ENS-PSL. Supervised by Luc Segoufin.
Applied Computer Science
- OS (Timothy Bourke)
- Numerical System
- Compilation (Jean-Christophe Filliâtre)
Formal & Algorithmic CS
- Algorithmic (Tatiana Starikovskaya, Pierre Aboulker)
- Lambda-Calculus (logic) (ENS Paris-Saclay, Jean Goubault-Larrecq)
- Formal Language & complexity theory (Michaël Thomazo)
- Advanced Complexity (MPRI)
- Combinatorial Optimisation (Chien-Chung Huang)
Selected Projects
You can find my main public projects on GitHub.
Nanyang Technological University, Singapore
From my internship at NTU, supervised by Prof. CONG Gao and PhD. SHI Jiachen.
- First version of a What-If for Column-oriented database.
ENS Paris, IASD M2, France
Projects made with peers from the M2; please check each report for collaborator details.
- A pair-trading dataset maker relating global opinion to polymarket price timeseries.
- A Word2Vec implementation in PyTorch.
- A Kernel method for movie recommendation.
- A GAN trained with multiple gaussians.
- A robust model that uses Canny Edge as a layer to counter-part gradient-based attack.
ENS Paris, PSL University, France
Projects made with Nathan Boyer and Grégoire Le Corre.
- A DeepQ-RL model applied to a car trying to learn to drive.
- A Diffusion Model presentation and application. The code implements the first paper by Ho et al.
- A GIT developed in C++, supporting server, branches, merges, etc.
- A Graph network applied to detect fake news.