TODAY, Wednesday, February 19th, at 3:30 PM , the DeCenter Seminar Series continues with Elaine Shi , a professor of Computer Science and Electrical & Computer Engineering at Carnegie Mellon University. She is interested in cryptography, game theory, algorithms, and the foundations of blockchains. She will present a seminar titled "Decentralized Mechanism Design: Cryptography Meets Game Theory." The event will take place in the Computer Science Building Room 105 . Abstract: In classical auction design, we take it for granted that the auctioneer is trusted and always implements the auction’s rules honestly. This assumption, however, no longer holds in modern auctions based on blockchains, or those mediated by third-party platforms such as Google. For example, in blockchain-based auctions, the consensus nodes that partly serve as the auctioneer are incentivized to deviate from honest behavior if profitable. Third-party auction platforms such as Google have also been involved in high-profile anti-trust lawsuits for manipulating their auctions. In this talk, I will describe our recent work on decentralized mechanism design, where we aim to build a new scientific foundation for emerging auctions that are not backed by a trusted auctioneer. I will characterize the mathematical landscape of decentralized mechanism design, by showing several infeasibility and feasibility results. I will also highlight how cryptography can play an essential role for bypassing impossibility results in decentralized mechanism design, leading to a new class of auctions that not only incentivize bidders to act honestly, but also incentivize the auctioneer to play by the book. Bio: Elaine Shi is a Professor at CMU. Prior to joining CMU, she was an assistant professor in UMD and an associate professor in Cornell. Her research interests include cryptography, security, algorithms, game theory, and foundations of blockchains. Elaine’s work has successfully transitioned cryptography and privacy algorithms from on-paper theory to large-scale real-world deployment. For example, her Oblivious RAM algorithm now serves as the backbone of Signal’s private contact discovery service and has also been implemented by Meta. Her differential privacy algorithm has been improved and implemented by companies such as Google and JP Morgan and is a core to Google’s Spanish Gboard. Elaine is a Packard Fellow, a Sloan Fellow, and an ACM Fellow. She has also received several awards such as an ONR YIP award, the NSF CAREER award, and various best paper awards such as the CCS Test of Time award, the NSA Best Scientific Cybersecurity paper, Top Picks in Hardware and Embedded Security, ASPLOS best paper, and others. We hope to see you there!