Esmaeil Keyvanshokooh

Esmaeil Keyvanshokooh 

Esmaeil Keyvanshokooh
Assistant Professor of Operations Management
Department of Information & Operations Management
Mays Business School, Texas A&M University
E-mail: keyvan-at-tamu-dot-edu
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About Me

I am an Assistant Professor of Operations Management at the Department of Information & Operations Management of the Mays Business School, Texas A&M University. I received my Ph.D. degree in Operations Research at the Department of Industrial & Operations Engineering of the University of Michigan at Ann Arbor. I earned a MSc in Statistics at the Department of Statistics of the University of Michigan, and a MSc in Industrial Engineering and Operations Research from the Iowa State University. I worked as a Machine Learning & Operation Research Analyst at Norfolk Southern Corporation, Atlanta, Georgia.

About My Research Interests

  • My research interests lie at the interface of statistical machine learning and optimization. In particular, I am interested in developing data-driven sequential decision-making methodologies under an uncertain environment and prove theoretical performance guarantees for them. My research is motivated by many real-world problems with both practical impact and interesting theoretical challenges.

    • Methodologies: Data-Driven Optimization, Machine Learning, Reinforcement Learning & Multi-armed Bandits, Causal Inference.

    • Applications: Healthcare Analytics and Operations, Medical Decision-Making, Business Analytics, Operations Management.

  • More information on my work can be found on my publication page and Google Scholar.

Selected Honors and Awards

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

    • For the paper: Contextual Learning with Online Convex Optimization with Applications to Medical Decision-Making.

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

    • For the paper: Contextual Learning with Online Convex Optimization with Applications to Medical Decision-Making.

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

    • For the paper: Contextual Learning with Online Convex Optimization with Applications to Medical Decision-Making.

  • Finalist, INFORMS Decision Analysis Society (DAS) Best Student Paper Competition, 2020.

    • For the paper: Contextual Learning with Online Convex Optimization with Applications to Medical Decision-Making.

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

    • For the paper: Contextual Learning with Online Convex Optimization with Applications to Medical Decision-Making.

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

    • For the paper: Advance Online Scheduling with Overtime: a Primal-Dual Approach.

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

    • For the paper: Coordinated and Priority-based Surgical Care: An Integrated Distributionally Robust Stochastic Optimization Approach.

  • University of Michigan Rackham Pre-doctoral Fellowship Award, 2019.

Selected Professional Service

  • Journal Referee for Management Science, Operations Research, Manufacturing & Service Operations Management, Production & Operations Management, Naval Research Logistics, IISE Transactions, Healthcare Management Science, European Journal of Operational Research, Optimization Letters, etc.

  • Judge for MSOM Service Operations SIG Conference 2021-2022, MSOM Healthcare Operations SIG Conference 2022.