The author in Vienna

I am a PhD Candidate in Machine Learning at Imperial College London with Dr Stefanos Zafeiriou and Prof Michael Bronstein working on Geometric and Bayesian Deep Learning with applications to Computer Vision and network analysis. I am currently a Research Intern at Google AI in Machine Intelligence/Machine Perception for Fall 2018. Previously, I interned in Quantitative Research (Systematic Trading) at JPMorgan Chase & Co in London for the Summer 2018. I have been a research intern at Speechmatics (Cantab Research Ltd.) where I worked on improving the company’s recurrent neural network language models, and a Data Scientist at HarperCollins Publishers in London. 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).

See my Curriculum Vitae or my short Resume.

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 data science, computer vision, and medical research.


Mehdi Bahri (GitHub/LinkedIn/Quora).

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