Ph.D. student, Electrical Engineering and Computer Sciences, UC Berkeley.
Advised by Michael I. Jordan.
University of California, Berkeley 465 Soda Hall (AMPlab) Berkeley, CA 94720-1720 Email me at elalaoui at eecs dot berkeley dot edu
My research interests lie somewhere between mathematical statistics, optimization and theoretical computer science. My work is on the design and analysis of low complexity algorithms targeted at extracting information from noisy data, in a very broad sense. I spend my time thinking about how one can design an algorithm for data analysis that runs under constrained resources, could they be time, memory, a minimal level of statistical performance, amount of randomness or amount of communication; and how to optimally tradeoff between these resources/constraints.
Ahmed El Alaoui, Xiang Cheng, Aaditya Ramdas, Martin J. Wainwright, Michael I. Jordan: Asymptotic behavior of -based Laplacian regularization in semi-supervised learning, (Submitted) [arxiv].
Tim Hunter, Ahmed El Alaoui, Alex Bayen: Computing the log-determinant of symmetric, diagonally dominant matrices in near-linear time, [arxiv].
CS174 Combinatorics and Discrete Probability (spring 2015).
I am a third year Ph.D. student in Electrical Engineering and Computer Science at the University of California at Berkeley. I did my master's at Ecole Normale Supérieure and my undergrad at Ecole Polytechnique. I wrote my master's dissertation on probabilistic record linkage while working at Ecole des Ponts with Guillaume Obozinski.
M.Sc. Mathématiques, Vision et Apprentissage, Ecole Normale Supérieure/Ecole des Ponts Paristech, 2013.
Eng.Deg. Applied math, Ecole Polytechnique, 2012.