Cynthia Rush is the Howard Levene Assistant Professor of Statistics at Columbia University. Originally from North Carolina, she completed undergraduate coursework at the University of North Carolina at Chapel Hill where she obtained a B.S. in Mathematics and in May of 2016 received a Ph.D. from Yale University under the supervision of Andrew Barron.
Professor Rush’s 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, she has obtained sharp theoretical guarantees on the performance of message passing algorithms in these settings. In addition to algorithmic development, much of her work has used concentration of measure tools and applied probability ideas to extend performance guarantees of such algorithms to the non-asymptotic regime. Rush is excited to continue exploring these areas in her future work and for the opportunity to apply these tools to new problems.