Esmaeil Keyvanshokooh - Publications

Published and Accepted Papers

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

• Contextual Learning with Online Convex Optimization: Theory and Application to Medical Decision-Making,
  Management Science, to appear.
  E. Keyvanshokooh, M. Zhalechian, C. Shi, MP. Van Oyen, P. Kazemian.
  (In collaboration with Massachusetts General Hospital).

  • 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.

• 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).

  • Special Issue: Advancing Pandemic Preparedness Through Data Analytics and Operations Research.

Under Revision/Review Papers

• Data-Driven Counterfactual Optimization for Personalized Clinical Decision-Making,
  Under Review, 2023
  C.-Y. Liao, E. Keyvanshokooh, G.-G. P. Garcia.
  

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

• Safe Reinforcement Learning with Contextual Information: Theory and Application to Personalized Comorbidity Management,
  Under Review, 2023
  J. Cao, E. Keyvanshokooh, T. Liu (The first two authors have equal contributions).

Working Papers

• Contextual Recourse Bandits: Optimizing Decisions through Counterfactual Explanations,
  Preliminary version: Accepted at CIST 2023,
  R. Gao, J. Cao, E. Keyvanshokooh (All three authors have equal contributions).

• Improving Treatment Responses via Limited Nudges: A Learning Approch,
  K. Gan, E. Keyvanshokooh, X. Liu, S. Murphy.

• Distributional Fairness for Counterfactual Explanation with Model Uncertainty,
  C.-Y. Liao, E. Keyvanshokooh, G.-G. P. Garcia.

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]