Professor Jensen's current research focuses on the discovery of causal knowledge from large and complex data sets. His work has applications in social network analysis, fraud detection, web mining, and analyzing large computing systems. Analyzing such data poses unique challenges and opportunities for machine learning, data mining, and AI. Other research interests include relational learning, statistical inference in machine learning algorithms, research methods in computer science, evaluation of AI systems, and computing and public policy. Professor Jensen serves on the Executive Committee of the ACM Special Interest Group on Knowledge Discovery and Data Mining and on the program committees of the International Conference on Machine Learning and the International Conference on Knowledge Discovery and Data Mining. He is an associate editor of ACM Transactions on Knowledge Discovery from Data. He was a member of the 2006-2007 Defense Science Study Group, and he currently serves on DARPA's Information Science and Technology (ISAT) Group. He is a member of the American Association for Artificial Intelligence and the ACM Special Interest Group on Knowledge Discovery in Databases.
Other
Resisting Structural Reidentification Anonymized Social Networks (with Michael Hay, Gerome Miklau, Don Towsley, and Philipp Weis), Computer Science Department Faculty Publication Series (2008)
We identify privacy risks associated with releasing network data sets and provide an algorithm that...
Anonymizing Social Networks (with Michael Hay, Gerome Miklau, Philipp Weis, and Siddharth Srivastava), Computer Science Department Faculty Publication Series (2007)
Advances in technology have made it possible to collect data about individuals and the connections...
Using Structure Indices for Efficient Approximation of Network Properties (with Matthew J. Rattigan and Marc Maier), Computer Science Department Faculty Publication Series (2006)
Statistics on networks have become vital to the study of relational data drawn from areas...
A Note on the Unification of Information Extraction and Data Mining using Conditional-Probability, Relational Models (with Andrew McCallum), Computer Science Department Faculty Publication Series (2003)
Although information extraction and data mining appear together in many applications, their interface in most...