Rachael Sexton is a NIST mechanical engineer in the Information Modeling and Testing Group of the Systems Integration Division, currently researching the usability of natural language processing for mining useful data for Smart Manufacturing Systems. His interests include machine learning, Bayesian Optimization, optimal control, hybrid physics/data-driven modeling, and anthropology. Prior to joining NIST, Rachael worked as a researcher at Arizona State University’s Design Informatics Lab in the Mechanical Engineering department, where he studied computational models of crowd-sourced human search strategies in complex design and control spaces using Gaussian Process Regression.