- 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.
Substantive areas: digital marketing, mobile advertising, targeting, personalization, privacy, online auctions.
Methods: policy evaluation, structural models, machine learning, reinforcement learning, mechanism design, causal inference.
Rafieian, Omid, and Yoganarasimhan, Hema, "Targeting and Privacy in Mobile Advertising."
Marketing Science, Vol 40(2), pp 193-218. (Lead article)
Rafieian, Omid, and Yoganarasimhan, Hema, "Variety Effects in Mobile Advertising."
Journal of Marketing Research, Volume 59, Issue 4, pp 718-738.
Rafieian, Omid, "Optimizing User Engagement through Adaptive Ad Sequencing."
Marketing Science, Accepted.
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.
Rafieian, Omid, "Revenue-Optimal Dynamic Auctions for Adaptive Ad Sequencing."
Rafieian, Omid, Kapoor, Anuj, and Sharma, Amitt, "Multi-Objective Personalization of the Length and Skippability of Video Advertisements."
Work in Progress
Bondi, Tommaso, Rafieian, Omid, "Privacy Regulation and Inference-Based Content Strategies: Polarization, Pricing & Consumer Welfare."
Rafieian, Omid, "Value of Perfect User Tracking in Ad Personalization."
Rafieian, Omid, "Geographical and Behavioral Information: Complements or Substitutes in Personalized Policies?"