Title: Graphical Models for Intelligence Collection
Speaker: Ned Dimitrov (Operations Research & Industrial Engineering, UT Austin)
In many intelligence agencies, the screening of data into usable information ready for analysis poses a significant bottleneck. Typically, much more data is available than what can be screened in the allotted time. We call the staff who screen raw data into usable information processors. We formulate the problem faced by an intelligence processor--selecting which data to screen--as an exploration-exploitation problem: the collector has to choose between exploring for new sources of relevant information and exploiting known sources.
To address the exploration-exploitation problem, we develop a mathematical model of the collector?s knowledge and examine algorithms that allow the collector to maximize the discovery of relevant data given a time limit. We computationally test the model and gain insight into solutions using a simulated intelligence data set based on the Enron social network and email corpus.
Dr. Dimitrov is an Assistant Professor in the Graduate Program in Operations Research & Industrial Engineering at the University of Texas at Austin. Prior to joining UT, for four years, he was an Assistant Professor in the Operations Research Department at the Naval Postgraduate School in Monterey, California. He received a Ph.D. in Theoretical Computer Science from the University of Texas at Austin (2008) and B.S. degrees in Mathematics and Computer Science from the University of Michigan, Ann Arbor (2002). He teaches courses in Computational Optimization, Network Flows and Graphs, Stochastic Combinatorial Optimization, Statistics, and Operations Management. His research focus is on optimization, with applications in infectious disease control and national security.
Homepage: <a href="http://neddimitrov.org">http://neddimitrov.org</a>
8:15am to 9:30am