Uribe's poster, titled “Non-asymptotic Convergence Rates in Distributed Learning," was one of 40 presented by students from all over world from a variety of interdisciplinary areas.
His research includes understanding rates of convergences. He looks for connections with other algorithms to understand how fast they work and why they work. These alogrithms are used by phones, planes, and satellites to detect patterns in movement. His advisors, Associate Professor Angelia Nedich and Assistant Professor Alexander Olshevsky are both part of the Department of Industrial and Enterprise Systems Engineering.
The conference was a good experience for Uribe. “It was interesting to see because it is a different audience than I am used to,” he said. “The more pure math, or applied math people were interested.”