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Rad Niazadeh is an Associate Professor at the University of Chicago Booth School of Business, with a courtesy appointment as faculty at the Toyota Technological Institute Chicago. He received his PhD in Computer Science, with a minor in Applied Mathematics from Cornell University. Niazadeh's research focuses on the interaction between algorithms, data, and incentives in real-time operations management. His primary goal is to develop theoretical methodologies and application-based frameworks for data-driven sequential decision-making, particularly in complex dynamic operational scenarios often related to online platforms, electronic markets, and non-profit organizations. He has published in prominent journals such as Management Science and Operations Research, and his research has received several accolades, including the INFORMS Auctions Market Design Michael H. Rothkopf Junior Researcher Paper Prize in 2021. Rad has also contributed to a range of conferences in computer science, including ACM STOC and NeurIPS.
University of Chicago Booth School of Business • Chicago, IL
Teach and conduct research in operations management, focusing on algorithms and data-driven decision-making.
Google Research • New York, NY
Conducted research on market algorithms.
Stanford University • Stanford, CA
Conducted research in computer science.
The doctoral program at Booth is organized into 'dissertation areas' which include Accounting, Behavioral Science, Econometrics and Statistics, Finance, Marketing, and Operations Management.