Jeremy Bolton received his B.S. degree in computer engineering from the University of Florida, Gainesville, in 2003, and received his M.E. and Ph.D. degrees in computer engineering from the University of Florida, Gainesville, in 2009. His dissertation research was focused on developing applied statistical models for the use of data analysis including context-modeling, multiple instance learning, and hyperspectral image analysis. As a lecturer at Peabody College, his focus is supporting the Data Science curriculum and instructing related courses. Previously, he was an Associate Research Scientist in the Computational Science and Intelligence Lab in the Computer and Information Sciences and Engineering Department at the University of Florida. Previous and current research includes the development of algorithms, methodologies, and mathematical models with a wide range of computational applications. Some computer vision applications include modeling and analysis of Hyperspectral and Multispectral imagery, synthetic aperture radar (remote), ground penetrating radar, seismic data, and infrared imagery. Jeremy has worked on many successful remote sensing and landmine detection projects whose goals were the identification and remediation of landmines: Wide Area Airborne Minefield Detection, Science of Land Target Spectral Signatures MURI, Ground-Based Standoff Mine Detection System, and Vehicle-Mounted Mine Detection System. Algorithms that he has researched, developed, and assessed within these projects are now used in the field, thus assisting in global humanitarian de-mining efforts. Dr. Bolton is an active member in the machine learning, pattern recognition, remote sensing, and landmine detection communities: member of IEEE Computational Intelligence Society, IEEE Geoscience and Remote Sensing Society, IEEE Computer Society, and Society of Photographic Instrumentation Engineers.