Rad Niazadeh is an assistant professor in Operations Management. He studies the interplay between algorithms, incentives, and learning in online marketplaces, with a focus on applications in revenue management and market design. In particular, he is interested in algorithmic mechanism design and game theory, online learning theory and applications, online algorithms, and algorithmic aspects of machine learning in operations research.

Prior to joining Chicago Booth, Rad was a Motwani postdoctoral fellow at Stanford University (department of Computer Science) and a visiting researcher at Google Research NYC (market algorithms team). He received his PhD in Computer Science from Cornell University (minored in Applied Mathematics). Additionally, he holds M.Sc. and B.Sc. degrees in Electrical Engineering from Sharif University of Technology.

Professor Niazadeh’s research has been published in journals such as Operations Research, Journal of Machine Learning Research, Games and Economic Behavior, Journal of the ACM, and in (peer-reviewed) top conference proceedings such as ACM STOC, IEEE FOCS, NeurIPS, ICML, ACM EC, ACM-SIAM SODA and ITCS.

Rad has received the INFORMS Revenue Management and Pricing Dissertation Award (honorable mention) in 2018, the Google PhD Fellowship in Market Algorithms in 2016, Stanford Motwani fellowship in 2017, and Cornell Jacobs fellowship in 2012.

Research Interests

Algorithmic mechanism design and game theory; Online algorithms and optimization in markets and platforms; Online learning theory and applications in operations management; Algorithmic aspects of machine learning in operations management

Academic Areas

  • Operations Management

Selected Publications

Working Papers

2021 - 2022 Course Schedule

Number Course Title Quarter
36920 Online Optimization - Applications in Operations Mgmt 1 2022 (Winter)
36921 Online Optimization - Applications in Operations Mgmt 2 2022 (Spring)