Adam Meyerson received his PhD from Stanford University in Fall 2002, with a thesis on approximation algorithms for design of minimum-cost computer networks. He spent the 2002-2003 academic year as a postdoctoral fellow of the Center for Algorithmic Adaptation, Dissemination, and Integration (Aladdin) at Carnegie-Mellon University. He joined the faculty of UCLA in Fall of 2003. Major research results include the first constant approximation for buy-at-bulk network design, the first online algorithm for the facility location problem, and the first constant approximation for orienteering. Recently he has focused on randomized online algorithms, making substantial progress towards the randomized k-server conjecture, devising a randomized algorithm for online matching, and introducing a new model for time-sensitive dynamic online problems. As of summer 2011, Adam has joined the engineering team at Google Mountain View. He is now working on improving ads quality.