The Homeland Security and Military Transformation Lab at George Mason University is a focal point for research on the application of decision and inference support technology to problems of:
o Protecting the U.S. homeland
o Transforming the U.S. military force to meet the military challenges of the 21st Century.

Research Topics
o Decision architecture for target discrimination
o Tracking and classification of time critical ground targets
o Multi-source information fusion
o Decision support for military situation assessment
o Evidence marshalling for intelligence analysis
o Military systems acquisition
o Analysis of force structure alternatives for U.S. ground forces

Faculty associated with the Lab

o Dr. K.C. Chang, Associate Professor. Dr. Chang performs research on multi-source information fusion. He has worked extensively on problems of combining information from multiple sources to draw inferences about the behavior of military forces. Current research includes the development of decision architecture for target discrimination for the Missile Defense Agency (MDA) Hercules project. Another active focus is the tracking and classification of time critical ground targets under DARPA Dynamic Tactical Targeting.

o Dr. Kathryn Blackmond Laskey, Associate Professor. Dr. Laskey has performed extensive research on the application of Bayesian inference and decision theory to problems of military situation awareness. She assisted in the development of SiteProfiler(R) an antiterrorism risk management system for military bases. She has performed research on an inference system for detecting and predicting the behavior of time-critical targets. She is currently working on a project to develop an information architecture for missile defense. Another project involves the use of information markets to aggregate information for forecasting political and military events. Dr. Laskey has published extensively and given frequent presentations on Bayesian decision theoretic methods applied to homeland security and military situation awareness.

o Dr. Andrew Loerch, Associate Professor. Dr. Loerch performs research on optimization of U.S. force structures to meet the military challenges of the 21st Century. He has developed and published methods for incorporating missions other than war into analyses to support decisions by the U.S. military on the structure of military forces.

o Dr. David Schum, Professor.Dr. Schum’s work focuses on evidence marshalling for intelligence analysis. He has performed extensive work with various intelligence agencies on evidential and inferential matters

Graduate students associated with the Lab

o Dave Brown - Application of Bayesian networks to improving the efficiency of models and simulations for military systems acquisition decision making
o Forrest Crain (PhD Spring 2003) - Comparison of methods for assessing weights for multiattribute decision analysis
o Pam Hoyt - Interleaving structure learning with discretization for learning mixed discrete and continuous Bayesian networks.
o Steven M. Charbonneau, LTC, US Army - Optimal placement of sensor clusters in support of ground operations. The methodology incorporates the effect of terrain and weather on acoustic and seismic transmissions.
o Stephen Cannon - Evaluation of exact and approximate inference methods for dynamic Bayesian networks for multi-source information fusion
o Ning Xu - Application of Bayesian learning technology to discretizing continuous variables in dynamic Bayesian networks for multi-source information fusion
o Pranathi Pendyala - Application of Bayesian learning technology to discretizing continuous variables in dynamic Bayesian networks for multi-source information fusion
o Wei Sun - Development of efficient inference methods for dynamic Bayesian networks for multi-source information fusion
o Ghazi Alghamdi - Application of Bayesian networks to role-based access control in information systems