Congratulations to James Bocinsky who defended his Master’s thesis titled “Learning Multiple Target Concepts From Uncertain, Ambiguous Data Using The Adaptive Cosine Estimator and Spectral Match Filter” this week on Monday, March 11th. His research focused on developing algorithms for explosive hazard detection. His thesis included investigating multiple instance learning, clustering, and various target detection methods to aid in target detection and classification problems found in applications such as explosive hazard detection and hyperspectral target detection. In his proposed algorithms, he extended the existing Multiple Instance Adaptive Cosine Estimator and the Multiple Instance Spectral Match Filter algorithms from learning a single target concept into algorithms that can learn multiple target concepts.