The worst-case analysis of algorithms provides accurate guidance about how to solve some but not all computational problems. In this talk, I'll survey my recent work in three application domains where novel algorithm analysis frameworks enable meaningful performance guarantees: revenue-maximizing auctions, graph partitioning, and social network analysis.
Tim Roughgarden received his Ph.D. from Cornell University in 2002 and joined the Stanford CS department in 2004, where he is currently an associate professor. His research interests are in theoretical computer science, especially its interfaces with game theory and networks. He wrote the book "Selfish Routing and the Price of Anarchy" (MIT Press, 2005) and co-edited the book "Algorithmic Game Theory", with Nisan, Tardos, and Vazirani (Cambridge, 2007). His awards include the 2002 ACM Doctoral Dissertation Award (Honorable Mention), the 2003 Tucker Prize, a 2007 PECASE Award, the 2008 Shapley Lectureship of the Game Theory Society, the 2009 ACM Grace Murray Hopper Award, and the 2012 EATCS-SIGACT Godel Prize.