Abstract: The multi-armed bandit paradigm has been studied extensively for over 50 years in Operations Research, Economics and Computer Science literature, modeling online decisions under uncertainty in a setting in which an agent simultaneously attempts to acquire new knowledge and to optimize its decisions based on the existing knowledge. In this talk I'll discuss several new results motivated by web applications, such as content matching (matching advertising to page contest and user's profile) and efficient web crawling. Bio: Eli Upfal is a Professor of Computer Science at Brown University. He received his Ph.D. from the Hebrew University in Israel. before joining Brown in 1997, he was a research staff member at the IBM Research Devision, and a Professor of Applied Mathematics and Computer Science at the Weizmann Institute. His main research interests are randomized algorithms and probabilistic analysis, with applications to optimization algorithms, communication networks, parallel and distributed computing, and computational biology.