Kelvin Choi is an experienced IT professional based in Hong Kong with a strong blend of hands-on engineering and IT management across 16 years in IT support and services. In recent years he has focused on back-end development and contributed to the high-profile OpenVINO open-source toolkit, implementing and optimizing clDNN plugin features such as ScatterNDUpdate and GatherND and improving kernel reorders and performance-critical primitives. He brings practical expertise in bridging infrastructure-level optimizations with product-quality testing and static-analysis fixes, reflecting an attention to both performance and code quality. Holding an MBA from the University of Wales, Cardiff, Kelvin combines technical depth with business acumen to align engineering work to organizational goals. Colleagues can expect a steady, systems-minded engineer who prefers solving tricky low-level problems that have outsized impact on AI inference performance.
5 years of coding experience
7 years of employment as a software developer
Master of Business Administration - MBA, Master of Business Administration - MBA at University of Wales, Cardiff
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Role in this project:
Back-end Developer
Contributions:296 reviews, 27 commits, 104 PRs in 1 year 10 months
Contributions summary:Kelvin implemented and fixed clDNN plugin features for the OpenVINO toolkit related to the ScatterNDUpdate operation. Their work involved implementing the ScatterNDUpdate op, addressing Klocwork issues, and adding new operations such as GatherND. Furthermore, the user made changes to reorder kernels, optimized reorder between blocked and non-blocked formats and reorder between FC matmal and reshape primitives. These changes involved modifying kernel files and test cases.
Contributions:5 reviews, 8 PRs, 638 pushes in 4 years 2 months
pytorchdeep-learninggpuopenvino-toolkitinference
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