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Author: Salena Fitzgerald
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Mateo Diaz and Team
(From left to right) Jonathan Eckstein, who chairs the prize committee, is accompanied by author contributors Mateo Diaz, Miles Lubin, Haihao Lu, David Applegate, Oliver Hinder, and Miguel Anjos, who chairs the Mathematical Optimization Society.

A research team that includes Mateo Diaz, assistant professor in the Department of Applied Mathematics and Statistics, has won the 2024 Beale–Orchard-Hays Prize for Excellence in Computational Mathematical Programming. Conferred every three years by the Mathematical Optimization Society, the award recognizes the team’s groundbreaking work on Primal-Dual Linear Programming (PDLP).

Mateo Diaz’s team won the 2024 Beale–Orchard-Hays Prize for their work on Primal-Dual Linear ProgrammingThe prize was presented this summer at the International Symposium on Mathematical Programming, where the team was commended for “its long-term potential to make first-order methods a practical option to solve large-scale linear programming problems; its adaptability to GPUs and other parallel computing architectures; the careful algorithmic engineering work to make the methods practical; and the sophisticated and innovative analysis used to justify and describe the performance of the algorithms.”

Their code now ships with Google OR Tools (a software suite for optimization).