Alex Estes graduated from the University of Nebraska-Lincoln in 2013 with a B.S. in Mathematics and from the University of Maryland in 2018 with a Ph.D. in Applied Mathematics & Statistics and Scientific Computation under the supervision of Michael Ball. In his dissertation work, Alex studied optimization and data science methods to support Federal Aviation Administration decisions regarding air traffic management initiatives, which are actions that are taken to prevent excess congestion in the national airspace.
After graduation, Alex joined the Institute for Mathematics and its Applications at the University of Minnesota as a Target Industrial Postdoc. In this role, he conducted research at the University of Minnesota and applied optimization techniques at Target to assist in planning of distribution center operations and store stocking policies.
From 2020 to 2022, Alex was an assistant professor of Industrial and Systems Engineering at the University of Minnesota. In 2022, he joined the University of Maryland as an assistant professor with a joint appointment in the Institute for Systems Research and the Department of Decisions, Operations, and Information Technology in the Robert H. Smith School of Business.
His research interests include integrating prediction tasks with optimization to improve the quality of decisions made in the face of uncertainty while making efficient use of the available data, using optimization techniques to conduct data science tasks, and applications thereof in air transportation.
My research interests include discrete optimization, statistics, and data science, often with applications to air traffic management.