Aix-en-Provence, Provence-Alpes-Côte d'Azur, France
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Summary
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Rockstar
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Top School
Greg Heinrich is a research engineer with 14 years in software and over a decade in the semiconductor industry, now focusing on deep learning efficiency at NVIDIA. He blends low-level expertise in power management and device drivers with extensive ML engineering—designing distributed, reproducible data pipelines and optimizing neural networks for production (pruning, INT8 calibration, custom CUDA ops). An active contributor to NVIDIA DIGITS, he has helped improve image classification tooling and dataset workflows in a widely used open-source training system. Greg holds an MSc in Embedded Systems and a finance diploma from LSE, and is named on 11+ patents, reflecting a strong track record of applied innovation across SoC-to-shipment product cycles.
14 years of coding experience
18 years of employment as a software developer
London School of Economics and Political Science
Master of Science (MSc) Embedded Systems, Master of Science (MSc) Embedded Systems at ESIEE PARIS
Contributions:263 commits, 253 PRs, 57 pushes in 3 years
Contributions summary:Greg's contributions primarily involve enhancements to the image classification system within the NVIDIA Digits repository. They implemented features like displaying ground truth labels within the image classification interface. Furthermore, they worked on data processing tasks, including the removal of duplicate data input to C3 and enabling the use of server files for dataset creation. They also modified and improved the functionality of the combined graph and the underlying training tasks.
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