Academic Collaborators

Academic Collaborator

University

Department

Email

Arguello, Jamie University of North Carolina at Chapel Hill Information & Library Science jarguell@email.unc.edu
Armstrong, Helen NC State College of Design hsarmstr@ncsu.edu
Betancourt, Brenda University of Florida Statistics bbetancourt@ufl.edu
Boettcher, William NC State Public and International Affairs wboettch@ncsu.edu
Capra, Robert University of North Carolina at Chapel Hill Information & Library Science rcapra@unc.edu
Chi, Min NC State Computer Science mchi@ncsu.edu
Chirkova, Rada NC State Computer Science rychirko@ncsu.edu
Crouser, Jordan Smith College Computer Science jcrouser@smith.edu
Gotz, David University of North Carolina at Chapel Hill Information & Library Science gotz@unc.edu
Joines, Sharon NC State Design smbennet@ncsu.edu
Lahiri, Soumen Washington University in St. Louis Mathematics and Statistics s.lahiri@wustl.edu
Kaplan, Andrea Duke Statistics andrea.kaplan@duke.edu
Kapravelos, Alexandros NC State Computer Science akaprav@ncsu.edu
Menzies, Tim NC State Computer Science tjmenzie@ncsu.edu
Ottley, Alvitta Washington University in St. Louis Computer Science alvitta@wustl.edu
Park, Baekkwan East Carolina University Political Science parkb19@ecu.edu
Rand, William NC State Poole College of Management wrand@umd.edu
Simons-Rudolph, Joseph NC State Psychology jmrudolp@ncsu.edu
Sin, Steve University of Maryland START — Study of Terrorism and Responses to Terrorism sinss@umd.edu
Singh, Munindar NC State Computer Science mpsingh@ncsu.edu
Stolee, Katie NC State Computer Science ktstolee@ncsu.edu
van Gelder, Tim University of Melbourne Hunt Laboratory for Intelligence Research t.gelder@unimelb.edu.au
Wang, Yue (Ray) University of North Carolina at Chapel Hill Information & Library Science wangyue@email.unc.edu
Ware, Stephen University of Kentucky Computer Science sgware@cs.uky.edu
Wilson, Mark NC State Psychology mark@ncsu.edu

 

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LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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