3/7/19 | 4:15pm | E51-335
Reception to follow.
Assistant Professor of Operation Management
Abstract: The second price auction has been the prevalent auction format used by advertising exchanges because of its simplicity and desirable incentive properties. However, even with an optimized choice of reserve prices, this auction is not revenue optimal when the bidders are heterogeneous and their valuation distributions differ significantly. In order to optimize the revenue of advertising exchanges, we propose an auction format called the boosted second price auction, which assigns a boost value to each bidder. The auction favors bidders with higher boost values and allocates the item to the bidder with the highest boosted bid. We propose a data-driven approach to optimize boost values using the previous bids of the bidders. Our analysis of auction data from Google’s online advertising exchange shows that boosted second price auction with the data-driven optimized boost values outperforms the second price auction by up to 6%.
Bio: Negin Golrezaei is an Assistant Professor of Operations Management at the MIT Sloan School of Management. Her current research interests are in the area of machine learning, statistical learning theory, mechanism design, and data-driven optimization algorithms with applications to revenue management, pricing, and online markets. Before joining MIT, Negin spent a year as a postdoctoral fellow at Google Research in New York where she worked with the Market Algorithm team to develop, design, and test new mechanisms and algorithms for online marketplaces. She is the recipient of the 2017 George B. Dantzig Dissertation Award, the INFORMS Revenue Management and Pricing Section Dissertation Prize, University of Southern California (USC) Ph.D. Achievement Award (2017), USC CAMS Graduate Student Prize, for excellence in research with a substantial mathematical component (2017), USC Outstanding Teaching Award(2016), Marshall Ph.D. Teaching Award (2016), and USC Provost's Ph.D. Fellowship (2011). Negin received her BSc (2007) and MSc (2009) degrees in electrical engineering from the Sharif University of Technology, Iran, and a PhD (2017) in operations research from USC.