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Stephen Chestnut is a Senior Quantitative Researcher at G-Research, specializing in designing machine learning models for forecasting stock returns since May 2017. Prior experience includes a postdoctoral researcher role at ETH Zurich, focusing on operations research and theoretical computer science, and serving as a graduate research assistant at Johns Hopkins University, where research concentrated on streaming algorithms. Stephen has also held teaching assistant and instructor positions at Johns Hopkins University and the University of Colorado Boulder, covering various mathematics courses. Earlier in the career, Stephen worked as a scientist at ENSCO, Inc., developing algorithms for inertial navigation systems, and participated in an autonomous vehicle racing team. Stephen holds a Ph.D. in Applied Mathematics and Statistics from Johns Hopkins University, a Master's Degree in Applied Mathematics from the University of Colorado Boulder, and a Bachelor's Degree in Engineering Physics from Cornell University.