Shahine Bouabid

DPhil in Statistics student

About Me

I am a third year PhD student interested in applications of statistical machine learning to environmental sciences, supervised by Dino Sejdinovic and Athanasios Nenes. I am a Marie-Skłodowska Curie fellow, part of the iMiracli innovative training network of aerosols-cloud interactions and machine learning. Prior to that I graduated from Mathématiques, Vision, Learning (MVA) master at ENS Paris-Saclay and from Ecole Centrale-Supélec in applied mathematics.

Research Interests

I am interested in developing simple and interpretable statistical machine learning methodologies to address challenges that arise in environmental science. My recent work has focused on aggregate output learning for statistical downscaling and earth system emulation using physically-constrained models. The tools I use mostly draw from the theory of reproducing kernel Hilbert spaces and Gaussian processes, for which I enjoy a fond theoretical interest.

Contact Details

Office:  G.01

Pronouns: He/Him


Prof Dino Sejdinovic