Tamar
Cohen-Hillel

Assistant Professor, Division of Operations and Logistics
UBC Sauder School of Business

I am an Assistant Professor in the Division of Operations and Logistics at the UBC Sauder School of Business. I develop algorithmic and scalable optimization methods for complex operational decision problems in logistics, retail, and revenue management.

My research focuses on operational systems that are practically rich and computationally challenging, with an emphasis on approximation methods, decomposition approaches, and interpretable optimization models. I am especially interested in problems that appear intractable but contain hidden structure that can be leveraged for tractable, rigorous solution methods. My research has been published in Management Science, Manufacturing & Service Operations Management, and Mathematics of Operations Research.

Before joining UBC, I worked as a Research Scientist at Amazon. I received my Ph.D. in Operations Research from the MIT Operations Research Center, advised by Professor Georgia Perakis, and hold an M.Sc. in Information Management Engineering and a B.Sc. in Industrial Engineering from the Technion - Israel Institute of Technology.

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Portrait of Tamar Cohen-Hillel

Research

Logistics & Supply Chain Optimization

I study large-scale operational systems in logistics and supply chain management, with a focus on decomposition, dynamic planning, and decision-making under operational complexity. Recent work includes workforce planning, inventory optimization, and large-scale planning problems with complex operational structure.

Selected Work
  • Driving Efficiency: Optimizing Workforce for Last-Mile Deliveries
    with T. Cezik and L. Yedidsion. Working paper. Also relevant to Approximation & Scalable Optimization Methods.
  • Inventory Planning for Large Fulfillment Networks
    with B. Aghababaei. Work in progress.
  • Manager Behavior in the Product Replacement Problem: Addressing Preferences and Uncertainty
    with M. Moran-Pelaez and G. Perakis. Work in progress. Also relevant to Retail & Revenue Management.

Retail & Revenue Management

My work in retail and revenue management examines how customer behavior and demand dynamics interact with operational decision-making. I study pricing, promotions, and assortment-related problems using optimization models that balance operational realism with computational tractability.

Selected Work

Approximation & Scalable Optimization Methods

Across these application domains, my research focuses on scalable optimization methods for computationally challenging operational problems. I am particularly interested in approximation algorithms, decomposition techniques, and interpretable algorithmic approaches for large-scale systems.

Selected Work

Teaching

My teaching focuses on analytical decision-making, operations management, and optimization. Courses emphasize structured problem-solving, modeling intuition, and the development of analytical tools for complex operational and managerial settings.

Technical concepts are motivated through operational examples and real-world systems, with the goal of making rigorous quantitative methods accessible to students from diverse backgrounds and levels of technical experience.

Courses

Student Supervision

Bahareh Aghababaei (MSc)

Recognition

Grants

  • NSERC Discovery Grant and Launch Supplement (2023)

Research Awards

  • First Place, POMS College of Supply Chain Management Best Student Paper Award (2019)
  • First Place, INFORMS Service Science Best Cluster Paper Competition (2018)
  • First Place, Rothblum Award - ORSIS Prize for Excellence in Research in OR (2016)

Honors & Nominations

  • Nomination for the GCUS Teaching Excellence Award (2022)
  • Honorable Mention, MSOM Practice-Based Paper Competition (2019)
  • Finalist, INFORMS Service Science Best Service Science Paper Award (2019)
  • Finalist, INFORMS Social Media Analytics Section Best Student Paper Award (2019)
  • Finalist, POMS-JD.com Best Data-Driven Research Paper Competition (2019)
  • Finalist, POMS College of Behavior in Operations Management Junior Scholar Working Paper Competition (2019)
  • Nomination for the Goodwin Medal for Outstanding TA (2019)

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