About Justin Romberg's Work

My research interests lie on the boundaries between applied mathematics, signal processing, optimization, and machine learning. My recent work includes new techniques for solving certain kinds of nonlinear equations using convex programming, using randomized linear algebra to develop a new framework for array imaging, and methods for making neural networks more computationally efficient that come with mathematical guarantees of performance.

Awards and Achievements

IEEE Fellow

PECASE Award (2009)

Rice University Young Alumni Award (2010)