My name is Cynthia Rush and I am an Assistant Professor in the Department of Statistics at Columbia University. Originally from North Carolina, I completed my undergraduate coursework at the University of North Carolina at Chapel Hill where I obtained a B.S. in Mathematics and in May, 2016, I received my Ph.D. from Yale University under the supervision of Andrew Barron.
My research interests lie broadly in statistics and applied probability with a current focus on statistical machine learning algorithms, such as message passing. These algorithms can be used for inference and optimization in many applications including communications systems, compressed sensing, and image reconstruction. In recent work I have obtained sharp theoretical guarantees on the performance of message passing algorithms in these settings. In addition to algorithmic development, much of my work has used concentration of measure tools and applied probability ideas to extend performance guarantees of such algorithms to the non-asymptotic regime. I am excited to continue exploring these areas in my future work and for the opportunity to apply these tools to new problems.