The author in Vienna

I am a PhD Candidate in Computer Science at Imperial College London with Dr Stefanos Zafeiriou and Prof. Michael Bronstein working on Geometric Deep Learning, with applications to Computer Vision and network analysis.

Recently, I was a Research Intern at Google AI in Machine Intelligence/Machine Perception for Fall 2018 in New York City. Previously, I interned in Quantitative Research (Systematic Trading) at JPMorgan Chase & Co in London for the Summer 2018.

I graduated with an MSc in Advanced Computing from Imperial College London, and a Diplôme d’Ingénieur in Applied Mathematics and CS from Ensimag (Grenoble), both with Distinction.

I received a prestigious Qualcomm Innovation Fellowship in 2019.

See my Curriculum Vitae.

Current research interests

Besides what I do at work, I am interested in a variety of topics in Machine Learning, notably in statistical learning and optimisation.

  • Non-euclidean geometry in Machine Learning (manifold learning, Riemannian optimisation)
  • Approximate inference in probabilistic graphical models
  • Representation learning and component analysis
  • Tensor methods, sparse coding, compressed sensing (see my MSc thesis)
  • Social network analysis, more precisely influence propagation

My preferred applications are in, computer vision and medical research.


Mehdi Bahri (GitHub/LinkedIn/Quora).

Mail: mehdi [dot] b [dot] tn [at] gmail [dot] com