Esmaeil Keyvanshokooh - Publications

Working Papers

• Safe Reinforcement Learning with Contextual Information: Theory and Application to Comorbidity Management,
  J. Cao, E. Keyvanshokooh, T. Liu (The first two authors have equal contributions).

  • Second Place, POMS College of Healthcare Operations Management (CHOM) Best Paper Competition, 2024.

  • Selected for presentation at the Healthcare SIG Track at INFORMS MSOM 2024.

• Constraint-Aware Self-Improving Large Language Model for Clinical Role Model Generation,
  C.-Y. Liao, E. Keyvanshokooh, G.-G. P. Garcia.
  (In collaboration with Emory Global Diabetes Research Center).

  • Finalist, INFORMS Health Applications Society (HAS) Best Student Paper Competition, 2026 (Awarded to C.-Y. Liao).

• LIBRA: Language Model Informed Bandit Recourse Algorithm for Personalized Treatment Planning,
  J. Cao, R. Gao, E. Keyvanshokooh, J. Ma (all authors have equal contributions).
  

• Learning When to Nudge: A Dual-Agent Bandit Framework for Behavioral Interventions,
  E. Keyvanshokooh, K. Gan, Y. Guo, X. Liu, S. Murphy.

• Hidden Costs, Biased Decisions: Predicting and Optimizing E-Retailer Shipping Charges Under Information Asymmetry,
  Q. Zhu, E. Keyvanshokooh, G. R. Heim.

• Decarbonizing Critical Care to Achieve ‘‘Net Zero" Through Sustainable Operations Management,
  J. Qin, E. Keyvanshokooh, F. Sasangohar, F. Masud.
  (In collaboration with Houston Methodist Hospital).

  • Selected for presentation at the Healthcare SIG Track, MSOM Conference, 2026.

• Hospital Admission and Patient Transfer Control: An Offline Doubly-Robust Learning Approach,
  S.S. Ghasbeh, E. Keyvanshokooh, A. Dean, M. P. Van Oyen.
  

  • Second Place, INFORMS Health Applications Society (HAS) Best Student Paper Competition, 2026 (Awarded to S.S. Ghasbeh).

• Sequential Feature Acquisition for Treatment Assignment under Partial Observability,
  M. J. Lee, R. Gao, E. Keyvanshokooh.
  

  • Selected for presentation at the INFORMS Workshop on Data Science 2026.

• Online Uniform Sampling: Randomized Learning-Augmented Approximation Algorithms with Application to Digital Health,
  X. Liu, K. Gan, E. Keyvanshokooh, S. Murphy.

Published and Accepted Papers

• Last-Mile Humanitarian Logistics Planning with Isolated Communities,
  Manufacturing & Service Operations Management, to appear.
  M. Noorizadegan, M. Fattahi, E. Keyvanshokooh, J. Stauffer.
  (In collaboration with Honduras Red Cross).

• Augmenting Individualized Treatment Planning via Data-Driven Clinical Role Model Selection,
  Production & Operations Management, to appear. [DOI]
  C.-Y. Liao, E. Keyvanshokooh, F.J. Pasquel, G.-G. P. Garcia.
  (In collaboration with Emory Global Diabetes Research Center).

  • Selected for presentation at the Healthcare SIG Track at INFORMS MSOM 2026.

  • Honorable Mention, POMS College of Healthcare Operations Management (CHOM) Best Paper Competition, 2026.

  • Finalist, SMDM Lee B. Lusted Prize in Quantitative Methods & Theoretical Development, 2023 (Awarded to C.-Y. Liao).

• Contextual Learning with Online Convex Optimization: Theory and Application to Medical Decision-Making,
  Management Science, Vol. 71(2), 10442-10464, 2025. [DOI]
  E. Keyvanshokooh, M. Zhalechian, C. Shi, MP. Van Oyen, P. Kazemian.
  (In collaboration with Massachusetts General Hospital).

  • Media Coverage: Empowering Personalized Medicine: A Groundbreaking Data-Driven Solution for Optimizing Treatment and Dosage Decisions

  • Finalist, INFORMS Minority Issues Forum (MIF) Paper Competition, 2026.

  • Finalist, POMS College of Healthcare Operations Management (CHOM) Best Paper Competition, 2022.

  • Finalist, INFORMS MSOM Best Student Paper Competition, 2021.

  • Finalist, INFORMS Health Applications Society (HAS) Best Student Paper Competition, 2021.

  • Second Place, INFORMS Decision Analysis Society (DAS) Best Student Paper, 2020.

  • Winner, IOE Katta G. Murty Prize for Best Student Paper on Optimization, 2020.

• HR-Bandit: Human-AI Collaborated Linear Recourse Bandit,
  International Conference on Artificial Intelligence and Statistics (AISTATS 2025)
  J. Cao, R. Gao, E. Keyvanshokooh (all authors have equal contributions),
  (Preliminary version: Accepted at CIST 2023).

• Contextual Bandits with Budgeted Information Reveal,
  International Conference on Artificial Intelligence and Statistics (AISTATS 2024)
  K. Gan, E. Keyvanshokooh, X. Liu, S. Murphy.

• Data-Driven Hospital Admission Control: A Learning Approach,
  Operations Research, Vol. 71(6), 2111–2129, 2023. [DOI]
  M. Zhalechian, E. Keyvanshokooh, C. Shi, MP. Van Oyen,
  (In collaboration with St. Joseph Mercy Hospital).
  

  • Winner of IOE Richard C. Wilson Prize for Best Student Paper on Service Systems, 2021 (Awarded to M. Zhalechian).

• Online Resource Allocation with Personalized Learning,
  Operations Research, Vol. 70(4), 2138–2161, 2022. [DOI]
  M. Zhalechian, E. Keyvanshokooh, C. Shi, MP. Van Oyen,
  (In collaboration with Michigan Medicine).

• Online Advance Scheduling with Overtime: A Primal-Dual Approach,
  Manufacturing & Service Operations Management, Vol. 23(1), 246-266, 2021. [DOI]
  E. Keyvanshokooh, C. Shi, MP. Van Oyen,
  (In collaboration with Michigan Medicine).

  • Winner of IOE Richard C. Wilson Prize for Best Student Paper on Service Systems, 2019.

• Coordinated and Priority-based Surgical Care: An Integrated Distributionally Robust Stochastic Optimization Approach,
  Production & Operations Management, Vol. 31(4), 1510-1535, 2022. [DOI]
  E. Keyvanshokooh, P. Kazemian, M. Fattahi, MP. Van Oyen,
  (In collaboration with Mayo Clinic).
  

  • Winner of IOE Bonder Fellowship Award in Applied Operations Research, 2017.

• Mitigating the COVID-19 Pandemic through Data-Driven Resource Sharing,
  Naval Research Logistics, Vol. 71(1), 41-63, 2024. [DOI]
  E. Keyvanshokooh, M. Fattahi, K. Freedberg, P. Kazemian,
  (In collaboration with Massachusetts General Hospital and Harvard Medical School).

  • Among 7 papers accepted to the Special Issue: Advancing Pandemic Preparedness Through Data Analytics and Operations Research.

Healthcare Analytics & Medical Journal Papers

• A Responsible Framework for Assessing, Selecting, and Explaining Machine Learning Models in Cardiovascular Disease Outcomes Among People With Type 2 Diabetes: Methodology and Validation Study,
  JMIR Medical Informatics, Vol. 13, e66200, 2025. [DOI]
  Y. Yang, C.-Y. Liao, E. Keyvanshokooh, H. Shao, M. B. Weber, F. Pasquel, and G.-G. P. Garcia,
  (In collaboration with Emory Global Diabetes Research Center).

• Development and Evaluation of Cardiovascular Disease Risk Models for Patients with Type 2 Diabetes,
  Scientific Reports, Vol. 16 (1), 15574, 2026. [DOI]
  Y. Yang, T. Liu, C.-Y. Liao, S. J. Lee, E. Keyvanshokooh, H. Shao, M. B. Weber, F. J. Pasquel, and G.-G. P. Garcia,
  (In collaboration with Emory Global Diabetes Research Center).

Selected Published Papers (Prior my Ph.D. studies)

In my past research life, I used to work on the design and modeling of logistics and supply chain systems.

• An Optimization-based Approach for the Healthcare Districting under Uncertainty,
  S. M. Darmian, M. Fattahi, S.M. Seyed-Hosseini, E. Keyvanshokooh, Computers & Operations Research, Vol. 135, 2021. [DOI]

• Hybrid Robust and Stochastic Optimization Approach for Closed-loop Supply Chain Design Network using an Accelerated Benders Decomposition,
  E. Keyvanshokooh, S.M. Ryan, E. Kabir, European Journal of Operational Research, Vol. 249 (1), 76-92, 2016. [DOI]

• Supply Chain Network Design under Uncertainty: a Comprehensive Review and Future Research Directions,
  K. Govindan, M. Fattahi, E. Keyvanshokooh, European Journal of Operational Research, Vol. 263 (1), 108-141, 2017. [DOI]

• A Dynamic Pricing Approach for Returned Products in Integrated Forward/Reverse Logistics Network Design,
  E. Keyvanshokooh, M. Fattahi, S.M. Seyed-Hosseini, R. Tavakkoli-Moghaddam, Applied Mathematical Modelling, Vol. 37 (24), 10182-10202, 2013. [DOI]

• A Multi-stage Stochastic Program for Supply Chain Network Re-design Problem with Uncertain Price-dependent Demands,
  M. Fattahi, K. Govindan, E. Keyvanshokooh, Computers & Operations Research, Vol. 100, 314-332, 2018. [DOI]