CentraleSupélec engineering student with a focus on Artificial Intelligence and Data Science.
I work on practical machine learning projects involving data modeling, analysis, and reliability.
I build and study machine learning models with attention to both their performance and their robustness.
My work often involves connecting structured data with interpretability and real-world constraints.
Areas of interest:
- Deep learning applied to tabular and time-series data
- Retrieval and graph-based methods for knowledge representation
- Evaluation and reliability of AI models
- Applications in energy systems, environmental data, and industrial processes
| Project | Description | Tech Stack |
|---|---|---|
| wine-quality-forecasting | Predicts French wine quality from historical weather data (1950–2024). Focuses on data preparation, feature analysis, and neural network modeling. | PyTorch, Pandas, Plotly |
| STRM | Website for an electrical-services company, built with responsive design and client-managed content. | React, TypeScript, Tailwind, Vite |
Python · PyTorch · TensorFlow · Polars · SQL · React · TypeScript · Azure · Git
- CentraleSupélec – MEng, Artificial Intelligence and Data Science
- University of Tokyo – Exchange semester, Technology Management for Innovation (2025)