Justin Peel is an experienced software engineer with a strong background in digital signal processing, image processing, and machine learning algorithms. Previous roles include principal software engineer at Vivint Smart Home, where Justin architected embedded video solutions and designed machine learning pipelines, and software engineer at Raytheon Applied Signal Technology, focusing on the development of algorithms and software for digital communications and embedded systems. Justin also has a significant research background with internships at Sandia National Laboratories and Fermi National Accelerator Laboratory, as well as a PhD candidacy in Computational Physics, where work involved advanced quantum simulations. Currently, Justin is employed as a software engineer at Google, optimizing data pipelines and enhancing query performance for large datasets. Justin holds a Bachelor of Science degree in Physics from Idaho State University, graduating with a 3.9 GPA.
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