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Previous Student Research Projects
Developing Robust Reopening Processes following Natural Disasters
LTJG Christina Domanowski developed a robust optimization model to determine the best way to reopen essential services after a natural disaster. A case study was conducted for supermarkets in Wilmington, North Carolina after Hurricane Florence to demonstrate how robust optimization can improve access to food. This work was presented by ENS Domanowski at the 2020 INFORMS Annual Meeting and by Dr. Svirsko at the Dynamics of Disasters 2021 Conference and 2021 INFORMS Annual Meeting.
LTJG Domanowski was a Bowman Scholar of the Class of 2021 and received her masters degree in Applied Science (Operations Research) from the Naval Postgraduate School.
Data Analysis of Illegal Fishing Networks
Based on observations of fishing vessels in an area of the ocean, LTJG Eric Wilson developed a method to determine ship arrival rates and service rates. LTJG Wilson was an Operations Research Honors Student of the Class of 2021 and he is currently attending flight school.
Temporal Network Architectures of Neurocognitive and Psychological Symptoms in Collegiate Athletes with Sport-related Concussion
LTJG Caroline Turner developed a network model to understand the changes in relationships between psychological symptoms and neurocognitive domains before a concussion, immediately following the injury, and after recovery. LTJG Turner presented this work at the 2021 INFORMS Annual Meeting.
LTJG Turner was a Trident scholar of the Class of 2022 and received the Daughters of the American Revolution Prize for pursuing a major administrated by the mathematics department and excelling in the area of Operations Research. She will pursue a Master's in Public Policy at the University of Cambridge funded by the Karl F. Beyer Memorial Graduate Scholarship.
Allocation of Limited Search Assets in Undersea Warfare
LTJG D. Gray Benson developed an optimization model to determine the allocation of limited tactical search assets to detect targets in undersea warfare. He used a discrete-time Markov chain to model the movement of underwater targets and an integer program to determine the optimal routes for tactical search assets. This work was presented at the 2022 INFORMS Conference on Security.
LTJG Benson was a Bowman Scholar of the Class of 2022 and was selected by the mathematics department for the Military Operations Research Society award for his work. He will be attending power school this fall.
Allocation of Surveillance and Search Assets in Undersea Warfare
ENS Sebastian Martin (coadvised with Dr. Daphne Skipper) developed an optimization model to place surveillance sensors and expanded on optimal search formulation by LTJG Gray Benson to include operational constraints of tactical search assets. This work was presented at the 2023 and 2024 INFORMS Annual Meeting.
ENS Martin was a Trident Scholar of the Class of 2024 and was selected by the mathematics department for the Military Operations Research Society award for his work. His was a finalist for the INFORMS Undergraduate Operations Research Prize.
Improving Access to the Midshipmen Development Center
ENS Ford Knippa (co-advised with Dr. Brice Nguelifack and LT Ryan Bailey) was a 2024 Bowman Scholar. As part of his Bowman project, Ford developed a discrete-event simulation model of the Midshipmen Development Center (MDC) and explored alternative scheduling policies to increase provider availability. Ford is currently at NPS pursuing a master’s in Operations Research.
Strategic Staging of Tactical Search Assets in Undersea Warfare
ENS Abby Morgan developed an optimization model that determines staging locations for tactical search assets given the location of surveillance assets in order to maximize the probability of contact with an adversary target. This work will be presented at the 2026 INFORMS Annual Meeting.
ENS Morgan was a Bowman Scholar of the Class of 2026. She will be attending power school this fall.
Allocation of Limited Search Assets in Undersea Warfare
ENS Graham Rose developed a two-stage sequential simulation-optimization model that determines where to place active and passive sensors to maximize the probability of detecting an intelligent adversary target. This work will be presented at the 2026 Winter Simulation Conference.
ENS Rose was a Bowman Scholar of the Class of 2026. He will be attending power school this fall.
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