Portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 1
Short description of portfolio item number 2 
Published in Naval Research Logistics, 2024
Spatiotemporal vaccine allocation policies for epidemics with behavioral feedback dynamics.
Recommended citation: Barth, J., Li, S., Aprahamian, H., & Gupta, D. (2024). Spatiotemporal vaccine allocation policies for epidemics with behavioral feedback dynamics. Naval Research Logistics, 71(1), 109–139. https://doi.org/10.1002/nav.22142
Published in INFORMS Journal on Data Science, 2024
An optimization-based order-and-cut approach for fair clustering of data sets.
Recommended citation: Li, S., Aprahamian, H., Nouiehed, M., & El-Amine, H. (2024). An optimization-based order-and-cut approach for fair clustering of data sets. INFORMS Journal on Data Science, 3(2), 124–144. https://doi.org/10.1287/ijds.2022.0005
Published in Naval Research Logistics, 2024
A network-based optimization approach for quantifying the benefits of customized vaccination strategies.
Recommended citation: Li, S., & Aprahamian, H. (2024). Quantifying the benefits of customized vaccination strategies: A network-based optimization approach. Naval Research Logistics, 71(1), 64–86. https://doi.org/10.1002/nav.22134
Published in IISE Transactions, 2024
An optimization-based framework for minimizing disease spread in social networks with heterogeneous nodes.
Recommended citation: Li, S., & Aprahamian, H. (2024). An optimization-based framework to minimize the spread of diseases in social networks with heterogeneous nodes. IISE Transactions, 56(2), 128–142. https://doi.org/10.1080/24725854.2023.2191668
Article in Advance, INFORMS Journal on Computing, 2026
A spatial branching method for robust group testing design under uncertainty in prevalence rates and dilution behavior.
Recommended citation: Li, S., Aprahamian, H., & Chatterjee, S. (2026). A convex relaxation-based spatial branching approach for optimal robust group testing designs under prevalence rate and dilution behavior uncertainty. INFORMS Journal on Computing. Article in Advance. https://doi.org/10.1287/ijoc.2023.0465
Working paper, 2026
Boundary-price decomposition and policy-column algorithms for nested Markov decision processes.
Recommended citation: Li, S., Toumazis, I., & Schaefer, A. J. (2026). State-action-induced nested Markov decision processes: Boundary-price decomposition and policy-column algorithms. Working paper.
Working paper, 2026
Shape-constrained approximate linear programming with Chvátal–Gomory basis functions.
Recommended citation: Li, S., & Schaefer, A. J. (2026). Shape-constrained approximate linear programming for integer-resource Markov decision processes via Chvátal–Gomory basis functions. Working paper.
Working paper, 2026
A win-probability Markov decision model for automated ball-strike challenge strategy.
Recommended citation: Li, S., Powers, S., & Schaefer, A. J. (2026). Optimizing automated ball-strike challenges in Major League Baseball: A win-probability Markov decision model. Working paper.
Submitted to Radiotherapy & Oncology, 2026
Long-term dysphagia outcomes after treatment for oropharyngeal cancer.
Recommended citation: Li, S., Jang, I., Barbon, C. E. A., Moreno, A. C., Schaefer, A. J., Lee, J. J., Lai, S. Y., Fuller, C. D., Hutcheson, K. A., & Manduchi, B. (2026). Tumor burden and early swallow recovery predict imaging-graded dysphagia at 2- and 5-years after treatment for oropharyngeal cancer. Submitted to Radiotherapy & Oncology.
Working paper, 2026
A decision-analytic model for optimizing the diagnostic management of pulmonary nodules found through screening.
Recommended citation: Li, S., Toumazis, I., Schaefer, A., Ishizawa, S., Ozik, J., Collier, N. T., Meza, R., Lam, S., & Khattra, S. (2026). A decision-analytic model to optimize diagnostic management for screen-detected pulmonary nodules. Working paper.
Presentation: Accepted at WCLC 2026 (World Conference on Lung Cancer).
Submitted to JCO Oncology Practice, 2026
Digital-twin and optimization methods for reducing MRI changeovers and increasing appointment availability.
Recommended citation: Li, S., Schaefer, A. J., Jaffray, D. A., Siewerdsen, J. H., & Yung, J. P. (2026). Digital twin and optimization-guided MRI patient sequencing to reduce changeover and increase appointment-slot availability. Submitted to JCO Oncology Practice.
Recognition: Selected for Best of Professional at AAPM 2026 (American Association of Physicists in Medicine); accepted at RSNA 2026 (Radiological Society of North America) Annual Meeting.
Submitted to Operations Research, 2026
A dual approximate linear programming approach for revealing state-relevance weights.
Recommended citation: Li, S., Ciré, A., Diamant, A., & Sarhangian, V. (2026). Revealing state-relevance weights in dual approximate linear programming. Submitted to Operations Research. https://doi.org/10.48550/arXiv.2608.24629
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Invited presentation at the 2022 INFORMS Annual Meeting in Indianapolis, Indiana.
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Session Chair for the session Breaking the Chain: Using OR to Control Infectious Outbreaks at the INFORMS Annual Meeting 2023.
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Invited presentation at the 2023 INFORMS Annual Meeting in Phoenix, Arizona.
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Invited presentation at the 2024 International Symposium on Mathematical Programming in Montréal, Canada.
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Session Chair for the session Strengthening Healthcare Systems for Preparedness at the INFORMS Annual Meeting 2024.
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Invited presentation at the 2024 INFORMS Annual Meeting in Seattle, Washington.
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Invited presentation at the 2025 INFORMS Computing Society Conference in Toronto, Canada.
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Invited presentation at the 2025 Canadian Operational Research Society Annual Conference in Edmonton, Canada.
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Session Chair for the session Modeling for Mitigation: Designing Disease Control Protocols at the INFORMS Annual Meeting 2025.
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Invited presentation at the 2025 INFORMS Annual Meeting in Atlanta, Georgia.
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Invited presentation at the 2026 INFORMS Annual Meeting in San Francisco, California.
Teaching Assistant, Texas A&M University, 2022
Served as a Teaching Assistant for undergraduate and graduate courses in industrial engineering and operations research at Texas A&M University from May 2022 through December 2023.
Instructor, Rice University, 2025
Instructor at Rice University from August 2025 through December 2026.