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  • Cornell Tech,
    Bloomberg Center 471,
    2 West Loop Road,
    New York, NY 10044

Omid Rafieian

  • Assistant Professor of Marketing
  • Demir Sabanci Faculty Fellow of Marketing and Management
  • Cornell Tech and SC Johnson College of Business, Cornell University


My research interests broadly encompass topics related to digital marketing, mobile advertising, personalization, and privacy. I examine these topics through two complementary lenses – (1) how can we utilize the recent advancements in machine learning to create value in digital marketplaces, and (2) how can we use theory-driven structural frameworks to study the marketing and economic implications of such developments.

Research Interests

Substantive areas: digital marketing, mobile advertising, targeting, personalization, privacy, online auctions.

Methods: policy evaluation, structural models, machine learning, reinforcement learning, mechanism design, causal inference.



Doctor of Philosophy

in Marketing
University of Washington


Bachelor of Science

in Applied Mathematics
Sharif University of Technology


Rafieian, Omid, (2023) "Optimizing User Engagement through Adaptive Ad Sequencing."
Marketing Science, Volume 42, Issue 5, pp 910-933.

Rafieian, Omid, and Yoganarasimhan, Hema, (2022) "Variety Effects in Mobile Advertising."
Journal of Marketing Research, Volume 59, Issue 4, pp 718-738.

  • Finalist, AMA-MRSIG Don Lehmann Award, 2023
  • Rafieian, Omid, and Yoganarasimhan, Hema, (2021) "Targeting and Privacy in Mobile Advertising."
    Marketing Science, Volume 40, Issue 2, pp 193-218. (Lead article)

  • Winner, Frank M. Bass Dissertation Paper Award,2021
  • Finalist, John D.C. Litte Best Paper Award, 2021
  • Chapters and Survey Papers

    Rafieian, Omid, and Yoganarasimhan, Hema, "AI and Personalization."
    To appear in Review of Marketing Research, Special Issue on Artificial Intelligence in Marketing,
    Editors Sudhir, K, and Toubia, Olivier.

    Working Papers

    Work in Progress

    Rafieian, Omid, and Zuo, Si, "Personalized Algorithms and the Virtue of Learning Things the Hard Way."

    Rafieian, Omid, "Value of Perfect User Tracking in Ad Personalization."

    Rafieian, Omid, "Geographical and Behavioral Information: Complements or Substitutes in Personalized Policies?"