Stanford Networking Seminar

12:15PM, Thursday November 12, 2009
Packard 202

Modeling large complex networks

Jure Lescovec
Stanford University

About the talk:
Large complex networks like online social networks, web graphs, Internet and biological networks share many common structural features, like the small-world phenomena or heavy tailed degree distributions. I will survey the work in this area and focus on the following questions: What do real graphs look like? How do they evolve over time? How can we generate synthetic, but realistic looking, networks? In addition, how can we do so with a mathematically tractable model that allows for rigorous analysis of network properties? Can we estimate such models from data?

About the speaker:
Jure Leskovec is an Assistant Professor of Computer Science at Stanford University. His research focuses on mining and modeling large social and information networks, their evolution, and diffusion of information and influence over them. Problems he investigates are motivated by large scale data, the Web and on-line media. He received three best paper awards and a ACM KDD dissertation award, won the ACM KDD cup in 2003 and topped the Battle of the Sensor Networks 2007 competition. Jure also holds three patents and is a program co-chair for the Machine Learning and Data Mining track at the upcoming World Wide Web conference.