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David Maughan is a Machine Learning Scientist at Rincon Research Corporation, where contributions include researching and developing Simultaneous Localization and Mapping (SLAM) techniques using various technologies, optimizing Iterative Closest Point algorithms, and creating data visualization tools. Previous experience includes an internship at Rincon Research Corporation, during which David Maughan developed code for object identification and similarity scoring with OpenCV. As a researcher at DGCAMP, David Maughan was awarded funding for a proposal on spacetime symmetries, published research, and presented at multiple conferences. David Maughan also worked as a Computational Science Researcher at BYU, developing computational electrodynamics code for modeling black holes. Educational credentials include a Bachelor of Science in Mathematics and Physics from Utah State University and a Master's degree in Electrical Engineering and Machine Learning from the University of Arizona.