Andrew H is a quantitative researcher at Citadel Securities with nine years of software and research experience, blending a Caltech CS and Information & Data Science background with production-facing modeling for options market making and semi-systematic alpha. He has a strong track record applying machine learning and computer vision to real-world systems—from improving AR calibration and 6DoF pose estimation at JPL to deploying TensorFlow models at scale in biomedical imaging—bringing both research rigor and engineering discipline. Prior roles at Facebook, Lockheed Martin, and autonomous systems projects show his ability to move prototypes into robust, real-time pipelines, while his published work on feature extraction and pose acquisition highlights a commitment to reproducible research. Based in Palo Alto, he combines quantitative finance expertise with a deep systems and ML toolkit, often favoring solutions that reduce manual calibration and automate complex perception tasks.
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