Sicong Li is a Senior Software Engineer based in Cambridge with 7 years’ experience building and optimizing machine learning and computer vision software at Arm. He blends hands-on implementation (OpenCL, NEON) with tooling work—improving model accuracy evaluation and image tensor generation in the Arm NN ecosystem—to make ML inference more robust and reproducible. An Imperial College computer science graduate with a background in motion-data research and undergraduate teaching, he brings both rigorous technical foundations and clear communication skills to complex problems. Notably, he has a track record of fixing subtle bugs (e.g., out-of-bounds access) and enhancing developer tooling and documentation, helping teams trust and scale model evaluation pipelines.
6 years of coding experience
4 years of employment as a software developer
Master’s Degree, Computer Science, Master’s Degree, Computer Science at Imperial College London
Arm NN ML Software. The code here is a read-only mirror of https://review.mlplatform.org/admin/repos/ml/armnn
Role in this project:
ML Engineer
Contributions:7 commits in 1 month
Contributions summary:Sicong primarily contributed to the Model Accuracy Tool and ImageTensorGenerator, key components for evaluating the performance of machine learning models within the Arm NN framework. Their work involved refactoring code, incorporating image preprocessing techniques, and enhancing the tool with features like category-based evaluation, blacklist support, and range selection. They addressed a bug related to out-of-bound access within the ModelAccuracyChecker, ensuring the tool's robustness. Moreover, the user focused on improving the ImageTensorGenerator by fixing data type issues and adding documentation.
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