Academic Collaborators

Academic Collaborator University Department Email
Bail, Chris Duke Sociology and Public Policy
Boettcher, William NC State Political Science
Cardenas, Alvaro UT-Dallas Computer Science
Crouser, Jordan Smith College Statistical and Data Sciences
Desmarias, Sarah NC State Psychology
Eger, Markus NC State Computer Science
Feng, Jing NC State Psychology
Green, Nancy UNC-Greensboro Computer Science
Healey, Chris NC State Advanced Analytics
Hoggan, Chad NC State Adult Education
Jameson, Jessica NC State Communication
Joines, Sharon NC State Industrial Design
Keyton, Joann NC State Communication
Kowolenko, Mike NC State Computer Science
Lahiri, Soumen NC State Statistics 
Lester, James NC State Computer Science
Mayer, Roger NC State Management, Innovation and Entrepreneurship
Mayhorn, Chris NC State Psychology
Mayorga, Maria NC State Industrial and Systems Engineering 
Meade, Adam NC State Psychology
Menzies, Tim NC State Computer Science
Murphy-Hill, Emerson NC State Computer Science 
Nance, Mark NC State Public & International Affairs
Potts, Colin NC State Computer Science
Rand, William University of Maryland Center for Geospatial Information Science
Reeves, Galen Duke University Electrical and Computer Engineering and Statistics 
Reiter, Mike UNC Computer Science
Samatova, Nagiza NC State Computer Science
Shahzad, Muhammad NC State Computer Science
Simons-Rudolph, Joe NC State Psychology
Singh, Munindar NC State Computer Science 
Staddon, Jessica NC State Computer Science
Steorts, Rebecca Duke University Statistical Science
Tateosian, Laura NC State Geospatial Analytics 
Tyler, Beverly NC State Management, Innovation and Entrepreneurship
Viniotis, Yannis NC State Electrical and Computer Engineering
Vogel, Kathleen University of Maryland Public Policy
Wijesekera, Duminda George Mason Computer Science
Wilson, Alyson NC State Statistics
Wilson, Mark NC State Psychology
Young, Michael NC State Computer Science

Connect With Us

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.

If you would like to sign up for our email distribution list, please fill out this form: