Ming Lin
CPU Debug Software Technologist at Intel Corporation
California, United States
Summary
🤩
Rockstar🎓
Top SchoolMing Lin is a seasoned CPU debug software technologist and web application manager at Intel with 11 years of engineering experience focused on low-level systems, WebAssembly, and ML inference tooling. He’s an active open-source contributor who helped bring hardware-accelerated ONNX Runtime to the web via the WebNN Execution Provider and upgraded opset and operator support—including enabling models like Segment Anything—to run faster in browsers. His work spans rigorous spec-level test automation for WebAssembly and WAVM SIMD tests, plus front-end web-platform test contributions for emerging sensor and presentation APIs, showing a rare blend of backend, QA, and front-end expertise. Based in California and holding an M.S. in Electrical and Electronics Engineering from UW–Madison, he pairs deep protocol-level knowledge with practical engineering that bridges browser standards and machine learning execution.
11 years of coding experience
Master's degree Electrical and Electronics Engineering, Master's degree Electrical and Electronics Engineering at University of Wisconsin-MadisonMarquette University
Github Skills (22)
javascript10
testing10
machine-learning10
onnx10
simd10
webassembly10
webtest10
test-automation10
c-language9
memory-management9
control-flow9
deep-learning9
cprogramming-language9
html9
emscripten9
Programming languages (12)
Github contributions (5)
web-platform-tests/wpt
Jun 2016 - Dec 2020
Test suites for Web platform specs — including WHATWG, W3C, and others
Role in this project:
Front-end Developer
Front-end DeveloperContributions:98 reviews, 130 commits, 297 PRs in 4 years 7 months
Contributions summary:Ming primarily contributed to the development and testing of Web Platform Tests (WPT) related to various web APIs, including Presentation API, Battery Status, Remote Playback, Wake Lock API, Geolocation Sensor, and others. Their work involved adding and modifying Web IDL tests to align with the latest specifications and ensure accurate implementations. The user focused on creating and updating test files for different sensor APIs, custom elements, and feature policy implementations. They demonstrated a strong understanding of web standards and test automation.
microsoft-edgetest-runnerspecssafarifirefox
microsoft/onnxruntime
Apr 2023 - Mar 2025
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:237 reviews, 129 PRs, 529 comments in 1 year 11 months
Contributions summary:Ming primarily focused on enhancing the ONNX Runtime Web implementation to support hardware acceleration using WebNN API. They developed code to enable the WebNN Execution Provider, translating ONNX nodes using the WebNN API for hardware acceleration benefits. The user also upgraded the maximum supported ONNX opset to 19 and added support for various ONNX operators including Shape, Abs, Neg, various activation functions, Max, Min, and Reduce operations. Additionally, they integrated support for the Segment Anything model by adding new ops and data types.
runtimetrainingtensorflowai-frameworkaccelerator
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