Curriculum

Apr. 2025 - Sept. 2025 AI & Quantitative Research Intern at BNP Paribas Global Markets - Data & AI Lab, Frankfurt
May. 2024 - Aug. 2024 Machine Learning Research Intern at ENS Lyon, OCKHAM Team
Sept. 2023 - Apr. 2024 Student Researcher at LIRIS Laboratory, Lyon
Sept. 2024 - Mar. 2025 GRAF Program in Quantitative Finance at ISFA
Sept. 2021 - Sept. 2025 Engineering Student at Centrale Lyon
Sept. 2019 - July 2021 Mathematics and Physics (MPSI-MP*) at Lycée Mohammed VI d'Excellence

Projects

2048 — C++ Implementation

Recreated the 2048 puzzle with a clean, testable core engine (state, compression/merge, scoring), deterministic seeding, undo, and a lightweight TUI. Unit tests cover chains, no-move states, and spawn logic.

C++STLOOPUnit Testing

Ant Colony Optimization for Route Planning

Bio-inspired routing with pheromone evaporation/reinforcement balancing exploration vs exploitation; efficient convergence and visualizations across graph topologies.

PythonNumPyMatplotlibOptimization

Benchopt — Scalable Optimization Benchmarking

Contributions improving cross-platform compatibility and reproducibility; added features for performance tracking during the June 2024 coding sprint.

PythonBenchoptOptimizationReproducible ResearchOpen Source

CDS Pricing — Intensity vs Structural Models

Comparative framework with Merton-type models and Cox processes; Monte Carlo sensitivity to intensity, recovery, and volatility; calibration trade-offs highlighted.

PythonMATLABMonte CarloCredit RiskQuant Finance

Exotic Options Pricing — Heston–Hull–White

Pricing engine for lookback, Asian, and barrier options under joint stochastic vol & rates; Monte Carlo optimization and calibration to CAC40/EURIBOR data.

PythonMonte CarloHestonHull–WhiteQuant Finance

nanochat — Minimal Chatbot Extensions

Extended Karpathy’s nanochat for multi-turn dialogue; improved preprocessing/tokenization, training stability, and lightweight evaluation/sampling tools.

PythonPyTorchGPT-styleTokenizationNLP

Wave Function Collapse + VQ-VAE

Integrated a learned discrete latent space (VQ-VAE) with WFC to accelerate constraint propagation and boost diversity while preserving structure.

PythonPyTorchVQ-VAEWFCGenerative

MLOps / Data Science Starter

Entry-level DS project scaffold: data ingestion & EDA, a simple training pipeline, Dockerized service for inference, and CI for lint/tests. Focus on DevOps/MLOps hygiene.

PythonDockerShellCIMLOps

Skills

Programming: Python (pandas, NumPy, scikit-learn, PyTorch), SQL, Git, Linux

Quant/DS: Time-series, bandits, optimization (Benchopt), backtesting, risk & pricing

Tooling: Jupyter, Docker, CI/CD (basics)

Publications & Talks

  • Deep Hedging with Frictions (talk) — Internal seminar, BNP Paribas Global Markets, 2025
  • Benchopt Coding Sprint — Contributor, June 2024

Contact