Category: Cadet Projects

We analyze the Army’s separation landscape from 2008-present for the office of the surgeon general in a way that enables understanding of the mental health diagnosis – readiness relationship so that we improve recruiting and retention to reduce first term attrition, burdens on the health care system, and impact on Army units.

A study attempting to understand the current landscape of women’s participation in the U.S. workforce, in 2022 by examining factors like means of transportation, state, and government assistance.​ Gaining insight into factors that impact women’s workforce participation serves to better guide policy and inform leaders on how to facilitate an inclusive workplace.​

This research provides a comprehensive proof of concept for automating hub processing in the Insider Threat Hub by developing a pipeline that harmonizes sensor-based decision support for soldiers in battlefield conditions. The model ingests data from several wearable technology stream for real-time health monitoring, analogous to hub processes ingesting disparate data streams for analysis and…

This research delves into the relationship between criminal recidivism and insider threat risk, particularly within the U.S. Army. The methodology employed in this research focused on machine learning techniques but now emphasizes Generalized Linear Models (GLMs), to analyze the data and identify predictors of recidivism, which we then relate to Insider Threat.

This paper presents a case prioritization system that utilizes a deep learning classification model trained on expert evaluated insider threat cases to label cases as “negligible”, “low”, “medium”, or “high” threat level. This classification model enables a partnership between machine and human that focuses human effort for the greatest impact.