Nicolas Chagnet, PhD
Nicolas Chagnet, PhD
Junior data scientist
I am a doctor in theoretical physics who transitioned to data science: from modeling black holes to optimizing IKEA's furniture ecosystem.

Projects

Forecast of energy demand in France. The data is periodically fetched from the European Network of Transmission System Operators for Electricity API and the model automatically re-trained.
More details in this blog post.

Applied deep learning methods to solve differential equations with applications in physics.
More details in this blog post.

Numerical simulation of Ising spins under thermal fluctuations showcasing the transition between ferromagnets and paramagnets. The simulation is achieved with both Monte-Carlo sampling methods and genetic algorithms.
More details in this blog post.

Content-based recommendation system of scraped arXiv articles. The model uses cosine similarity to recommend articles and topic clustering to encode authors by the topic in which they work.

This project is about finding optimal Pokemon teams using optimization solvers. An optimal team must maximize the base total stat while maximizing the type coverage to reduce weaknesses.

Simple AI agent learning to play the French dice game '421'. The game is implemented in the gymnasium environment and the agents are trained using Q-learning methods.

Analysis and visualization of Formula 1 data in the form of an interactive dashboard. The data is dynamically fetched from an SQLite database.