Rate My Professor Marwa Banna

Banna's research centers on high-dimensional probability theory, free probability theory, random matrix theory, and matrix concentration inequalities. These topics offer mathematical tools for handling complex high-dimensional data prevalent in data science, machine learning, neural networks, wireless communication, image processing, finance, and biology. Her scholarship has accumulated over 230 citations according to Google Scholar. Notable publications include "On the limiting spectral distribution for a large class of symmetric random matrices with correlated entries" (with F. Merlevède and M. Peligrad, Stochastic Processes and their Applications, 2015; 64 citations), "Limiting spectral distribution of large sample covariance matrices associated with a class of stationary processes" (with F. Merlevède, Journal of Theoretical Probability, 2015; 36 citations), "Bernstein-type inequality for a class of dependent random matrices" (with F. Merlevède and P. Youssef, Random Matrices: Theory and Applications, 2016; 32 citations), "Hölder continuity of cumulative distribution functions for noncommutative polynomials under finite free fisher information" (with T. Mai, Journal of Functional Analysis, 2020; 25 citations), and "Matrix Poincaré inequalities and concentration" (with R. Aoun and P. Youssef, Advances in Mathematics, 2020; 18 citations).