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
Publications
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.
Rafieian, Omid, and Yoganarasimhan, Hema, (2021) "Targeting and Privacy in Mobile Advertising."
Marketing Science, Volume 40, Issue 2, pp 193-218. (Lead article)
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
Rafieian, Omid, Kapoor, Anuj, and Sharma, Amitt, "Multi-Objective Personalization of Marketing Interventions."
Rafieian, Omid, "A Matrix Completion Solution to the Problem of Ignoring the Ignorability Assumption."
Rafieian, Omid, "Revenue-Optimal Dynamic Auctions for Adaptive Ad Sequencing."
Bondi, Tommaso, Rafieian, Omid, and Yao, Yunfei (Jesse), "Privacy and Polarization: An Inference-Based Framework."
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?"