Computer science studies optimization problems when the data is at hand. Mechanism design studies optimization problems when the data is in the hands of rational players, who may strategically lie about the data in their possession if this is in their interest.
The need for mechanism design arises in many contexts, such as auctions, voting, healthcare, and social networks. However, to be useful in practice, mechanism design must model the players (their rationality, their concerns about privacy, their propensity to collude, their limitation on computation, etc.) in a very resilient manner.
In this talk I shall focus on designing mechanisms when the players are rational in a very weak sense and hold totally arbitrary and unstructured possibilistic beliefs about each other. As a concrete example, I shall discuss a joint work with Silvio Micali and Rafael Pass about generating revenue in single-good auctions.
Jing Chen is an Assistant Professor in the Department of Computer Science at Stony Brook University. She is also an Affiliated Assistant Professor in the Department of Economics. Her major research interests are computational game theory, mechanism design, auctions, healthcare, and markets. Jing received her B.E. and M.E. in Computer Science from Tsinghua University, and her PhD in Computer Science from MIT (2012). Before joining Stony Brook in 2013, she did a one-year postdoc at the School of Mathematics in the Institute for Advanced Study.