Research Teams

The LAS 2021 research portfolio is divided into four specific research areas of interest: Analytic Rigor and Performance, Machine Learning Integrity, Data Triage and Influence.

Analytic Rigor and Performance (ARP)

LAS research in Analytic Rigor & Performance (ARP) seeks to improve intelligence analysis and analytic outcomes by helping analysts balance the need for analytic rigor with real-world constraints such as timeliness and resources, as well as identifying factors and interventions that can enhance analytic performance. ARP considers the intelligence analysis decision-making space as a collective “joint cognitive system” of [analytic environment/mission + tools/systems used+ analyst/human] together, in order to identify pressures that can cause risks to analytic rigor when applied to underlying weak points in this system and to measure how appropriate interventions may strength the entire system.

ARP Performers 

For more information, please contact Dr. Christine Brugh – csbrugh@ncsu.edu

Machine Learning Integrity (MLI)

LAS research in Machine Learning Integrity seeks to address analytic integrity, quality, and assurance issues inherent within machine learning approaches. We specifically seek to demonstrate practical applications of machine learning integrity concepts such as data labeling alternatives and model explainability to address problems in cyber network defense and countering foreign influence campaigns and more broadly address big data triage and reasoning challenges via the creation and analysis of knowledge graphs.

MLI Performers

For more information, please contact Ms. Lori Wachter – lwachte@ncsu.edu

Data Triage

In 2021, the Data Triage team will endeavor activities that support the goal of implementing techniques required to meet the customers’ data needs while also adhering to Agency standards and infrastructure configuration.  As used by LAS, “triage” refers to the process of finding information of intelligence value within potentially very large data sets. LAS research in the domain of Data Triage seeks to improve analysts’ experiences in searching, exploring, and interacting with large datasets, as well as economizing and exploiting large datasets for analysis. The Data Triage activities are divided into two teams which will address data initiatives to advance methods to search, explore, prioritize, retain and extract value from large amounts of data in various formats. 

Data Triage Performers:

For more information on Data Triage, please contact Dr. Jascha Swisher – jdswishe@ncsu.edu or Ms. Lori Wachter – lwachte@ncsu.edu

Influence

LAS seeks to understand and characterize the phenomenon of influence operations in a variety of contexts, including foreign influence campaigns using social media, the identification of campaigns focused on a country’s leadership, the transfer of influence campaigns across platforms, and the measurement of the scope and effectiveness of foreign influence campaigns.

Influence Performers

For more information, please contact Dr. Christine Brugh – csbrugh@ncsu.edu

Technical Reports

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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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