Geoffrey Ducournau, PhD

R&D engineer working where quantitative research meets applied ML — production-grade systems for finance and industry.

Quantitative Research: Statistical mechanics, stochastic processes, volatility modeling and market-microstructure theory — applied to market-making, signal generation and systematic alpha.

Applied ML: Transformer architectures, graph neural networks and vision models (YOLO/SAM) — for forecasting, anomaly detection, computer vision and structured prediction.

Academic: Active research collaborations with Tsinghua University and Paris-Saclay on complex systems, emergent behavior and market dynamics.