Auto-Bidding, Auctions, and Allocation in Internet Advertising: Fundamental results and new trends.
Internet ad auctions are a fascinating innovation with a huge impact. From both a system and an algorithmic/economic point of view, advertising systems involve the interplay of many components. I will give an overview of this interaction and describe some problems and theoretical results in this domain. This will include some well-known results on budget allocation, as well as new problems and results in the increasingly important domain of auto-bidding. Time permitting, we will discuss some new questions at the intersection of machine learning and mechanism design.
Aranyak Mehta is a Distinguished Research Scientist in the Market Algorithms team at Google Research in Mountain View, CA. His research interests lie at the intersection of Algorithms and Economics, with an emphasis on Auction Design, Online Matching, Allocation Algorithms, and connections to Machine Learning, and their applications in practice.