R.L. Breiger --
Funded Research Projects since 2010 (1)
Predicting Rare Events by Reducing Unlikely Cases and Decomposing Statistical Models. Awarded by the Intelligence Advanced Research Pojects Activity (IARPA), 2018-2019.
, Principal Investigator. Co-Principal Investigators: and . We formulate a new multi-method approach for the analysis of rare events. We develop methods to reduce the pool of possible candidate cases for likely incidents of rare events, develop methods to decompose the results of statistical models aimed at estimating effects associated with the prediction of rare events, and use Monte Carlo simulation methods to establish the statistical generalizability of our findings. This work contributes basic research insights leading to increased accuracy for rare events monitoring.
New Analytic Methods for the Exploitation of Open-Source Structured Databases on the Pursuit of WMD Terrorism. Basic Research Grant awarded by the Defense Threat Reduction Agency (DTRA), 2010-2016. ==> A brief 2016 article overviews several of the main research lines pursued.
, Principal Investigator. Co-Principal Investigators: , , , . This is a project of the University of Arizona in partnership with the University at Albany-SUNY and the National Consortium for the Study of Terrorism and Responses to Terrorism (START) at the University of Maryland. The research seeks to enhance and leverage existing open-source datasets on violent non-state actors in order to develop new analytical tools to model human networks engaged in the pursuit of chemical, biological, radiological, and nuclear (CBRN) weapons.
Unifying Approaches to Adversarial Modeling. Department of Homeland Security (DHS), Science and Technology Directorate, Office of University Programs Award Number 2012-ST-061-CS0001, Project 3.4, made to the National Consortium for the Study of Terrorism and Responses to Terrorism (START). 2015-2017.
, , and , Principal Investigators. The objective of this project is to bridge and unify important aspects of quantitative and qualitative approaches so as to predict relevant phenomena such as the impact of specific ideological components on propensity for attacks of specific types (defined both by target and method), as well as, simultaneously, to identify specific groups most likely to engage in particular types of adversarial activities.
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