About Me

I’m currently a PhD student in Machine Learning in Colorado Boulder University. I’ve graduated from Ecole Polytechnique with a degree in Computational Mathematics with a minor in Machine Learning and hold a master in “Mathematics, Computer Vision, and Learning” from ENS Paris-Saclay (aka ENS Cachan).

My interests mainly lie within applied artificial intelligence and machine learning; I worked on deep and hierarchical reinforcement learning as an intern in RIKEN AIP Labs, Tokyo. Currently, I’m exploring more ML techniques, especially Unsupervised Learning methods as part of my PhD, supervised by Claire Monteleoni.



  • Reinfocement Learning with Options
  • Policy Gradient Methods
    • Ayoub Ghriss, Van Huy Vo, Reinforcement Learning, MVA [PDF][Slides][code]
  • Deep Automatic Chord Recognition
  • Artistic Styles : Neural Style Transfer vs Generative Adversarial Networks
    • Object Recognition and Computer Vision, MVA [PDF][Slides][Code]
  • A Martingale Hypothesis Test
    • Master Thesis, Ecole Polytechnique [PDF] [Code]
  • Volatility Derivatives : Variance Swap
    • El-Ghali Lalami, Ayoub Ghriss, Financial Mathematics Project [PDF][Slides][Code]


  • Spectral Clustering for Online Face Recognition
  • Mixture of Probabilistic PCA
    • Probabilistic Graphical Models, MVA [PDF][Code]
  • SymSpell implementation, Lavenshtein Edit Distance
    • Used for tweets normalisation, NLP, MVA [Code]
  • Ant Colony Algorithm
    • Introduction to Python, ENSAE [PDF][Code]