Data Science
& Artificial
Intelligence
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I am a Data Science & AI Engineering student at Télécom Paris with a strong foundation in mathematics from MPSI/MP* preparatory classes. I am passionate about building intelligent systems that solve real-world problems.
My interests span machine learning, quantitative finance, and computer vision. I enjoy turning complex data into actionable insights and shipping production-ready solutions.
Master of Engineering — Data Science & AI
Specialisation in machine learning, deep learning, and large-scale data systems.
Preparatory Classes — MPSI / MP*
Intensive two-year programme in advanced mathematics, physics, and computer science preparing for the Grandes Écoles entrance examinations.
Quantitative trading framework with Heston stochastic volatility model and vectorised backtesting engine achieving 2,000× acceleration.
ST-GCN model for dual-hand arithmetic gesture classification. 93.6% accuracy, <10ms CPU inference per frame via asynchronous strided inference.
Operator-level latency profiling of 24 object detectors on a Tesla T4 with AMP, Conv-BN fusion and TensorRT optimizations reaching up to 5.6× speed-ups. I covered the DETR family and the shared benchmarking tooling.
Quantitative Research
Student Organisation — Télécom Paris
Led the financial strategy for the largest student-run corporate networking event at Télécom Paris.
Human Resources Department
Supported the HR analytics team in modernising internal reporting workflows.