> ayoub_
Pixel-art portrait of Ayoub Oulad AliRESEARCHER
PROFILE / ABOUT

Ayoub Oulad Ali

Applied Mathematics graduate student at Sorbonne Université and AI researcher at École Polytechnique / CMAP, working at the intersection of machine learning, applied mathematics and computational imaging.

Generative AIPhysics-Informed MLMedical Imaging
01

Research direction

My work focuses on mathematically grounded machine learning: generative models, physical constraints, uncertainty and data-efficient methods for scientific and biomedical imaging.

Read the research page →

02

Academic path

  • Sorbonne Université — MSc Applied Mathematics
  • École Polytechnique / CMAP — AI research
  • Université de Nîmes — Mathematics & Computer Science
03

Research areas

Generative models, VAEs, diffusion models, representation learning, Physics-Informed Machine Learning, Scientific ML, Bayesian Deep Learning, uncertainty quantification, explainable AI and medical imaging.