Research
I study how to make operational decisions when information about uncertainty is limited. My work develops robust optimization methods, scalable decision rules, and inference tools for healthcare operations, supply chains, and service systems.
Journal articles
Working papers and papers under review are not listed here.
Distributionally Robust Optimization with Integer Recourse: Convex Reformulations and Critical Recourse Decisions
Operations Research Letters, 107546 (2026).
Nonlinear Decision Rules Made Scalable by Nonparametric Liftings
Management Science, 71(4):3449–3471 (2025).
Robust Queue Inference from Waiting Times
Operations Research, 72(2):459–480 (2024).
On Finite Adaptability in Two-Stage Distributionally Robust Optimization
Operations Research, 71(6):2307–2327 (2023).
Sustainable Inventory with Robust Periodic-Affine Policies and Application to Medical Supply Chains
Management Science, 65(10):4636–4655 (2019).
Preprints
Scalable Finite Adaptability via Polyhedral Partition and Learning
Other publications
“Flipping Out for Probability” (2021), with Jill Wilson, David Morton, and Eloise Chudik. Proceedings of the 2021 IISE Annual Conference.
IISE Engineering Education Track Best Paper Award.
Member of the Management Science Reproducibility Collaboration in Fisar et al. (2024). “Reproducibility in Management Science.” Management Science, 70(3):1343–1356.