Sheroze Sheriffdeen is a research engineer with 11 years of experience bridging computational science and applied computer vision, currently advancing embedded ML and gaze-input systems at Meta Reality Labs in Seattle. Trained at Cornell and UT Austin, his work blends Bayesian uncertainty quantification, state estimation, and physics-informed machine learning with real-time systems and automatic differentiation for vision optimization. He has a track record of moving academic research into production contexts—spanning plane-wave scattering and cosmology UQ to practical gaze and embedded-ML pipelines. Known for connecting rigorous numerical methods (e.g., dimensionality reduction and numerical linear algebra) to hands-on engineering challenges, he brings both deep theory and systems-level delivery to product-focused research.
11 years of coding experience
7 years of employment as a software developer
Master of Science - MS Computational Science Engineering and Mathematics, Master of Science - MS Computational Science Engineering and Mathematics at The University of Texas at Austin
Bachelor’s Degree Computer Science, Bachelor’s Degree Computer Science at Cornell University
Contributions:32 commits, 25 pushes, 1 branch in 1 year 4 months
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