Background
I am a Postdoctoral Fellow in the Department of Computational Applied Mathematics and Operations Research at Rice University and a Visiting Research Scholar at The University of Texas MD Anderson Cancer Center. I work with Dr. Andrew J. Schaefer at Rice and Dr. Iakovos Toumazis at MD Anderson.
Previously, I was a Postdoctoral Fellow in the Department of Mechanical and Industrial Engineering at the University of Toronto, working with Dr. Vahid Sarhangian, Dr. André Augusto Ciré, and Dr. Adam Diamant. I earned my Ph.D. in Industrial Engineering from Texas A&M University in 2024 under the supervision of Dr. Hrayer Aprahamian.
Research interests
My research in operations research and industrial engineering focuses on data-driven optimization for healthcare operations and public health decision-making.
Optimization under uncertainty
Optimization models and methods for decision-making under uncertainty, including robust group testing designs under prevalence rate and dilution behavior uncertainty.
Sequential decisions
Markov decision processes, approximate dynamic programming, and decomposition methods for nested Markov decision processes.
Healthcare operations
Decision support for healthcare scheduling and resource allocation, screening and diagnostic strategies, and infectious disease prevention and control.
My methodological interests also include combinatorial and network optimization and optimization for data analytics.
Current research
- Cancer imaging operations: Digital-twin and optimization-guided MRI patient sequencing to reduce changeovers and increase appointment-slot availability; submitted to JCO Oncology Practice, selected for Best of Professional at AAPM 2026, and accepted at the RSNA 2026 Annual Meeting.
- Cancer screening decisions: A decision-analytic model for optimizing the diagnostic management of screen-detected pulmonary nodules; accepted at WCLC 2026.
- Approximate dynamic programming: State-relevance weights, shape-constrained approximate linear programming, and decomposition algorithms for nested Markov decision processes.
Education
- Ph.D., Industrial Engineering, Texas A&M University, 2024 — GPA: 4.00/4.00
- M.S., Industrial Engineering, Georgia Institute of Technology, 2018 — GPA: 3.60/4.00
- B.Eng., Industrial and Systems Engineering, The Hong Kong Polytechnic University, 2017 — First Class Honors; minor in Software Engineering
Recognition and service
I was named the Outstanding Doctor of Philosophy in Industrial Engineering Student at Texas A&M University in 2023. I have chaired sessions at the 2023, 2024, and 2025 INFORMS Annual Meetings and serve as a peer reviewer for journals including INFORMS Journal on Data Science, Health Care Management Science, and INFOR: Information Systems and Operational Research.
Contact
Email: sl355@rice.edu