Bubacarr Bah

Research interests:

Compressed sensing (CS)

  • Sparse random matrices and expander graphs
  • Model-based CS with sparse matrices

Machine Learning

  • Linear embedding of high dimensional data
  • Dimensionality reduction

Random matrix theory with applications to CS and sparse approximation


Bubacarr received the BSc degree in mathematics and physics from the University of The Gambia in 2004, and the MSc degree in mathematical modeling and scientific computing from the University of Oxford, Wolfson College in 2008. He received his PhD in applied and computational mathematics at the University of Edinburgh in 2012 supervised by Prof. Jared Tanner. He was a postdoc with Prof. Volkan Cevher at LIONS, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, from 2012 to 2014. Later, until 2016 he was a postdoctoral fellow in the Mathematics Department at the University of Texas, TX. In June 2016 Bubacarr has been awarded the prestigious German Chair in Mathematics, valued at $700,000. The Humboldt Foundation gives the award to researchers wishing to work in the renowned African Institute for Mathematical Science in South Africa (AIMS – South Africa).


website: https://www.ma.utexas.edu/users/bah/
email: bah[at]math[dot]utexas[dot]edu
Curriculum Vitae



A. Kyrillidis; B. Bah; R. Hasheminezhad; Q. Tran Dinh; L. Baldassarre et al. : Convex block-sparse linear regression with expanders - provably. 2016. The 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadiz, Spain, May 7-11, 2016.
B. Bah; V. Cevher; S. Becker; B. Gözcü : Metric Learning with Rank and Sparsity Constraints. 2014. IEEE International Conference on Acoustics, Speech and Signal Processing, Florence, Italy, May 4-9, 2014.
B. Bah; L. Baldassarre; V. Cevher : Model-based Sketching and Recovery with Expanders. 2014. ACM-SIAM Symposium on Discrete Algorithms, Portland, Oregon, USA, January 5-7, 2014. p. 1529-1543. DOI : 10.1137/1.9781611973402.112.
B. Bah; A. Sadeghian; V. Cevher : Energy-aware adaptive bi-Lipschitz embeddings. 2013. 10th International Conference on Sampling Theory and Applications (SampTA), Bremen, Germany, July 1-5, 2013.