Shahine Bouabid

Shahine Bouabid

Kernel Methods, Bayesian Nonparametrics, Deep Learning, Aerosol-Cloud Interaction

I am a 1st year DPhil student in Statistics and part of the iMiracli training network, supervised by Profs. Dino Sejdinovic and Athanasios Nenes. I am interested in developing scalable and expressive statistical models allowing to account for the multiscale and multiresolution structure of climate data and better quantify our understanding of the aerosol-cloud effect on climate.

Publications

2021

  • S. L. Chau , S. Bouabid , D. Sejdinovic , Deconditional Downscaling with Gaussian Processes, in Advances in Neural Information Processing Systems (NeurIPS), 2021.

2020

  • P. Harder , W. Jones , R. Lguensat , S. Bouabid , J. Fulton , D. Quesada-Chacón , A. Marcolongo , S. Stefanović , Y. Rao , P. Manshausen , D. Watson-Parris , NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations, in NeurIPS Workshop on Tackling Climate Change with Machine Learning, 2020.
  • S. Bouabid , M. Chernetskiy , M. Rischard , J. Gamper , Predicting Landsat Reflectance with Deep Generative Fusion, in NeurIPS Workshop on Tackling Climate Change with Machine Learning, 2020.