Download CV

contact

  • or83@cornell.edu
  • 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

Biography

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.

Education

2020

Doctor of Philosophy

in Marketing
University of Washington

2015

Bachelor of Science

in Applied Mathematics
Sharif University of Technology

Publications

Rafieian, Omid, Kapoor, Anuj, and Sharma, Amitt, (2024) "Multi-Objective Personalization of Marketing Interventions."
Marketing Science, Forthcoming.


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, (2023) "AI and Personalization."
    Artificial Intelligence in Marketing, Review of Marketing Research, Vol. 20, pp. 77-102.

    Working Papers

    Rafieian, Omid, "A Matrix Completion Solution to the Problem of Ignoring the Ignorability Assumption."

  • Major Revision at Marketing Science

  • Bondi, Tommaso, Rafieian, Omid, and Yao, Yunfei (Jesse), "Privacy and Polarization: An Inference-Based Framework."

  • Major Revision at Management Science
  • Extended Abstract at 2024 ACM Conference on Economics and Computation (EC'24)

  • Rafieian, Omid, "Revenue-Optimal Dynamic Auctions for Adaptive Ad Sequencing."

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

    Work in Progress

    Ghili, Soheil, Rafieian, Omid, and Rashid, Mohammad, "Auctions Meet Bandits: The Role of Exploration in Advertising Auctions"

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

    Mosaffa, Mohammad, Rafieian, Omid, and Yoganarasimhan, Hema, "Media Bias in Visual Content: A Deep Learning Approach"

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