IACA Presentation

Was a pleasure to present at the 2014 Conference of the International Association of Crime Analysts. Talked about predicting crime using indicators extracted from social media [1]. Slides are attached to this post.


  1. [gerber2014predicting] Gerber, M., "Predicting Crime using Twitter and Kernel Density Estimation", Decision Support Systems (Elsevier), vol. 61, pp. 115-125, 2014.

Sociocultural Factors of Decision Making During Military Operations

Missions such as humanitarian intervention, security and defense support for civil authorities, and stability operations require Soldiers to make complex decisions in dynamic environments. Unfortunately, relatively little decision making research has focused on the Soldier’s/Commander’s own sociocultural attributes and how such attributes may affect decision making processes. To fill this gap, we are building statistical models of sociocultural attributes (or factors) hypothesized to play a role in Soldier/Commander decision making.

Automated prediction of adverse post-surgical outcomes

[hergenroeder2014automated] Hergenroeder, K., T. Carroll, A. Chen, C. Iurillo, P. Kim, Z. Terner, M. Gerber, and D. Brown, "Automated prediction of adverse post-surgical outcomes", Systems and Information Engineering Design Symposium (SIEDS), 2014: IEEE, 2014.

Automatic Detection of Cyber-Recruitment by Violent Extremists

[scanlon2014automatic] Scanlon, J., and M. Gerber, "Automatic Detection of Cyber-Recruitment by Violent Extremists", Security Informatics, vol. 3, issue 1, pp. 1-10, 12/2014.

Simulation Optimization of Police Patrol Districting Plans Using Response Surfaces

[zhang2014rsm] Zhang, Y., and D. Brown, "Simulation Optimization of Police Patrol Districting Plans Using Response Surfaces", SIMULATION: Transactions of The Society for Modeling and Simulation International, vol. 90, issue 6, pp. 687 - 705, 06/2014.

Qi Zhou

Qi joined the PTL in 2014 and is currently a first-year Master student. She received a Bachelor degree in Systems Engineering from UVA in 2013. Qi has research interests in data mining and predictive modeling.




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