Matthew Webb, PhD candidate at the MIT Center for Transportation & Logistics, has been selected by the Military Operations Research Society (MORS) as the 2026 winner of the Richard H. Barchi Prize for excellence in national security operations research.
Webb was nominated for the award on the strength of a paper he presented at last year’s MORS Symposium that applied a reinforcement learning (RL) framework to solve variants of the maximum flow network interdiction problem through the lens of the Russia-Ukraine conflict.
A traditional maximum flow network interdiction problem is modeled as a two-player simulation in which a network’s defender attempts to maximize flow through the network while an attacker attempts to minimize it. While Webb’s previous research had demonstrated the viability of RL agents in solving a standard, zero-sum version of the problem, real-world conflict scenarios are more complex and often feature belligerents with unique goals that are not simple inverses of each other. Drawing on a case study of the Ukraine rail network during the war with Russia, Webb developed an RL agent that could successfully learn to optimize network flow in the face of more realistic attacker behavior.
The MORS judges and Executive Committee selected Webb as the winner from among 19 nominees. Webb will formally receive the Barchi Prize and reprise his presentation at the 94th MORS Symposium, which will take place June 8-11, 2026, at the U.S. Air Force Academy.
Webb said he was grateful to be recognized for the prize, and for the support of his advisor, MIT CTL Executive Director Chris Caplice, as well as his thesis committee and the greater MIT CTL community.
“When I started my PhD in 2022, my primary goal was to develop research with tangible utility for our military personnel,” Webb said, “and this award is a meaningful validation of that mission.”
