Shouqun Liu is an engineering manager and W3C Advisory Committee representative based in California, leading ByteDance’s cross-platform framework team behind Lynx. With 11+ years of experience and a PhD from USTC, he brings deep systems and browser-engine expertise from roles as a Chromium/Blink committer and core contributor to the Crosswalk mobile web engine. He has led web technology teams at Xiaomi and contributed runtime, rendering and GPU acceleration optimizations across HTML5, WebGL and video playback. Shouqun also contributes to ML infrastructure on GitHub, including MXNet speech-model work, showing a rare blend of browser/runtime performance tuning and applied machine learning. Colleagues rely on him to bridge low-level engine internals with product-facing cross-platform frameworks that scale across mobile and embedded environments.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at University of Science and Technology of China
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:
ML Engineer
Contributions:6 commits, 9 PRs, 19 comments in 6 months
Contributions summary:Shouqun contributed to the `apache/mxnet` repository by implementing and debugging deep learning models, particularly related to speech recognition tasks. Their work included adding and modifying example scripts for speech demos, integrating with Kaldi features, and generating data processing utilities. The contributions also involved fixing shape issues in C++ package examples. The user also worked on converting Caffe models into the MXNet format.
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