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Itai Gurvich

Itai Gurvich

· James Allen Professor of Operations; Professor of Operations; Personnel Committee Member

Northwestern University · Management & Organizations

Active 2005–2026

h-index25
Citations2.2k
Papers8522 last 5y
Funding$867k

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Itai Gurvich is a Professor at the Kellogg School of Management, Northwestern University. He earned his Ph.D. from Columbia University’s Graduate School of Business in 2008 and joined Kellogg the same year. From 2016 to 2020, he was on the faculty of Cornell University’s campus in New York City (Cornell Tech) before returning to Kellogg in 2021. His research focuses on the performance analysis and optimization of processing networks, as well as the theory of stochastic-process approximations. His work has been recognized with the INFORMS Applied Probability Society’s Best Publication Award. Gurvich has served as the Stochastic Models Area Editor for Operations Research and as Chair of the INFORMS Applied Probability Society. His academic positions include roles at Northwestern University and Cornell University, with a background in Decisions, Risk and Operations, and Operations Research. His teaching interests encompass Operations Management, Service Systems, Queueing Systems, and Applied Probability.

Research topics

  • Computer Science
  • Mathematics
  • Mathematical optimization
  • Statistics
  • Mathematical economics
  • Economics
  • Operations research
  • Microeconomics
  • Applied mathematics
  • Geometry

Selected publications

  • Online Allocation and Pricing: Constant Regret via Bellman Inequalities

    Operations Research · 2021 · 37 citations

    Senior authorCorresponding

    We develop a framework for designing simple and efficient policies for a family of online allocation and pricing problems that includes online packing, budget-constrained probing, dynamic pricing, and online contextual bandits with knapsacks. In each case, we evaluate the performance of our policies in terms of their regret (i.e., additive gap) relative to an offline controller that is endowed with more information than the online controller. Our framework is based on Bellman inequalities, which…

    PublisherDOI

  • On the Optimality of Greedy Policies in Dynamic Matching

    Operations Research · 2023 · 26 citations

    Senior authorCorresponding

    Hindsight Optimality in Two-Way Matching Networks In “On the Optimality of Greedy Policies in Dynamic Matching”, Kerimov, Ashlagi, and Gurvich study centralized dynamic matching markets with finitely many agent types and heterogeneous match values. A matching policy is hindsight optimal if the policy can (nearly) maximize the total value simultaneously at all times. The article establishes that suitably designed greedy policies are hindsight optimal in two-way matching networks. This implies tha…

    PublisherDOI

  • Dynamic Matching: Characterizing and Achieving Constant Regret

    Management Science · 2023 · 22 citations

    Senior authorCorresponding

    We study how to optimally match agents in a dynamic matching market with heterogeneous match cardinalities and values. A network topology determines the feasible matches in the market. In general, a fundamental tradeoff exists between short-term value—which calls for performing matches frequently—and long-term value—which calls, sometimes, for delaying match decisions in order to perform better matches. We find that in networks that satisfy a general position condition, the tension between short…

    PublisherDOI

  • Dynamic Matching: Characterizing and Achieving Constant Regret

    SSRN Electronic Journal · 2021-01-01 · 18 citations

    articleOpen accessSenior author
    PublisherDOI

  • Dynamic Allocation of Reusable Resources: Logarithmic Regret in Overloaded Networks

    Operations Research · 2024-07-05 · 5 citations

    article

    How to dynamically allocate limited capacity to service requests? The problem studied in this paper is common in service applications, such as hotels, car rentals, and consulting services. These applications have limited capacity that must be allocated among incoming service requests. Different requests may require resources for varying durations, and some requests might yield higher rewards than others when fulfilled. The decision maker, who controls this capacity, must decide upon each request…

    PublisherDOI

Recent grants

Frequent coauthors

  • Jan A. Van Mieghem

    30 shared

  • R. Kannan Mutharasan

    Northwestern Medicine

    11 shared

  • Clyde W. Yancy

    Northwestern University

    6 shared

  • Nicholas D. Soulakis

    Northwestern University

    6 shared

  • Amy R. Ward

    University of Chicago

    6 shared

  • Eric Park

    Wake Forest University

    5 shared

  • Junfei Huang

    5 shared

  • Allen S. Anderson

    The University of Texas Health Science Center at San Antonio

    5 shared

Labs

  • Itai GurvichPI

Awards & honors

  • INFORMS Applied Probability Society’s Best Publication Award…
  • INFORMS The Operations Research Society of Israel Prize for…
  • POMS College of Healthcare Operations Management Best Paper…
  • NU Excellence in Research, Northwestern University

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