May 28, 2010 — Dr. James Caverlee has received a 2010 Defense Advanced Research Projects Agency Young Faculty Award (DARPA YFA) for his research on the social web and the technical challenges associated with realizing a new generation of applications suitable for monitoring, analyzing, and distilling information from massive-scale social systems.
Caverlee is an assistant professor of computer science and engineering at Texas A&M University and a researcher in the TEES Computer Science and Engineering Division.
DARPA presents the Young Faculty Award to outstanding junior faculty whose research will enable revolutionary advances in the areas of the physical sciences, engineering, and mathematics. The YFA program will fund Caverlee’s research through 2012.
"In the past few years, the Web has transformed into a fundamentally social platform for dynamic and ubiquitous real-time information." says Caverlee. "Hundreds of millions of users are actively engaged with social systems, placing huge demands on traditional approaches. How do we make sense of this deluge of social information?"
Caverlee’s work proposes that crowd-sourcing holds the key to effective dissemination of interesting and relevant real-time web information, and that efficient use of this information requires personalized crowd discovery based on an automated approach to identifying crowds and their significant characteristics in real time.
"Complementary to traditional web information applications that have focused on expensive off-line analysis of web data, our research goal is to fill the need for a new class of real-time web applications that must consume and process massive amounts of web data on-the-fly to provide users with important and relevant real-time information."
Potential defense applications include the automatic discovery of actionable information based on open source data (via Social Web mining), identification and tracking of online "hotspots" as they arise in real-time (e.g., disasters, terror attacks, civil uprisings), and adversarial network analysis for detecting clusters of coordinating attackers, among many other emerging social and mobile applications.
Caverlee received his Ph.D. from the Georgia Institute of Technology in 2007 and joined the faculty at Texas A&M shortly thereafter. His teaching and research interests include web-scale information management, distributed data-intensive systems, information retrieval, databases, and social computing.