Tina Li

Application Engineer

Minhang District, Shanghai, China
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Summary

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Rockstar
🎓
Top School
Tina Li is an Application Engineer with over a decade of hands-on experience designing and debugging mobile-phone and modem hardware, currently supporting Intel’s Mobile Communication Group in Shanghai. She combines deep PCB/schematic layout and production support expertise from earlier roles at SIMCOM with system-level hardware validation and customer-facing technology training. In recent years she has also contributed backend performance work to the popular OpenVINO open-source toolkit, applying low-level optimizations such as AMX-accelerated matrix routines and weight compression to boost inference performance. That blend of practical hardware design, field debugging, and low-level software performance tuning gives her a rare cross-disciplinary perspective useful for optimizing platform-level mobile solutions.
code11 years of coding experience
job4 years of employment as a software developer
book硕士, 电气, 硕士, 电气 at 西安交通大学
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Github Skills (14)

bfd10
matrix-multiplication10
c-language10
inference10
cprogramming-language10
performance-optimization10
openvino10
architecture9
computer-architecture9
intel9
deep-learning9
cpu-architecture9
mle8
ml8

Programming languages (6)

TypeScriptC++CJupyter NotebookMarkdownPython

Github contributions (5)

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openvinotoolkit/openvino

Jun 2021 - Jan 2023

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Role in this project:
userBack-end Developer & Performance Engineer
Contributions:651 reviews, 39 commits, 134 PRs in 1 year 6 months
Contributions summary:Tina primarily contributed to optimizing the OpenVINO toolkit, focusing on performance enhancements. Their commits reveal a deep understanding of low-level optimizations, including the use of AMX instructions for accelerating matrix multiplication within fully connected layers. The contributions include the fusion of multiple fully connected layers, code refactoring to improve efficiency, and the application of weight compression techniques. The user also worked on supporting new inference precisions, improving the performance of the Tensor Iterator.
inference-enginepytorchmodel-optimizerdeep-learninggpu
usstq/openvino

May 2021 - Apr 2025

OpenVINO™ Toolkit repository
Contributions:1 release, 5 PRs, 666 pushes in 3 years 11 months
pytorchdeep-learninggpuopenvino-toolkitcomputer-vision
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Tina Li - Application Engineer