Engineering student in the ModIA double diploma
(Modelling & AI — INSA Toulouse × ENSEEIHT, 2025–2028)

I come from an electrical engineering background (signal processing, embedded systems) and I'm moving into applied AI and data — the kind that solves concrete technical problems, not just fits a benchmark.

Looking for a 3-year AI/Data apprenticeship starting September 2026, based in Toulouse.

Datasheet Parser & Code Generator (in progress)
Built for the N7 Racing Team's BMS pole: a containerized Python tool that parses non-standardized component datasheets (PDF), can also generate .h header files if necessary. Functional prototype. Currently working on multi-format robustness and autonomous agent architecture with LLMs.
Python Podman PDF parsing LLM integration

TIPE — Space-Filling Curves & Image Compression
Replaced raster traversal with Hilbert/Morton/Peano curves in dithering algorithms.
Result: up to 89% lossless size reduction, with a consistent ~3.2% additional gain over linear scan for the same dithering method.
Python NumPy SciPy Jupyter

chip8-c
Working CHIP-8 interpreter in C with SDL3 — opcode decoding, memory layout, display timing.
C SDL3 emulator

• ModIA double diploma (INSA × ENSEEIHT) — 1st year electrical engineering, 2nd year full AI/data
• Contributing to N7 Racing Team (BMS + data telemetry integration)
• Taking Deep Learning with Python on Coursera (neural networks, Keras/PyTorch)
• Active in Toulouse tech community: AI-cionados meetups, Linux Embarqué meetups

Python · C · NumPy / SciPy / Scikit-learn · SQL · Git / GitHub Actions
Docker / Podman · Linux (Fedora) · MATLAB
In progress: Keras · PyTorch · LLM pipelines