Zach Grey is a research scientist in the applied and computational mathematics division at NIST Boulder. Zach's applied math research began in the Applied Mathematics and Statistics Department at Colorado School of Mines, where he qualified for a Ph.D. and transferred to finish the Ph.D. at University of Colorado Boulder (CU) Aerospace Engineering Sciences (following his research adviser, Professor Paul Constantine). Zach received a B.S. in aerospace engineering from Embry-Riddle Aeronautical University in 2010 and an M.S. in aeronautical and astronautical engineering from Purdue in 2015, which he earned while working full time at the Rolls-Royce corporation. His research involves model-based dimension reduction and manifold learning to facilitate novel explanations and interpretations related to artificial intelligence and machine learning. Specifically, he often works with data-driven applications involving image/signal processing, geometry and optimization.