Ming Lyu
算法专家 at NIO蔚来
Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolMing Lyu is an algorithm expert and software engineer with 11 years of experience bridging quantum physics, semiconductors, optics and production software. A Princeton PhD with roots at Tsinghua, he has moved from cleanroom fabrication and quantum-device simulation to building planning & control and redundant systems for autonomous driving at Pony.ai and NIO. He has practical mobile and tooling experience from a Google Flutter internship and notable contributions to the official flutter/plugins repo, improving e2e test reliability and performance monitoring. As a founding senior algorithm engineer at a startup he shaped foundational frameworks and control strategy, demonstrating both hands‑on implementation and system design. Based in Beijing, he blends deep physics intuition with pragmatic software engineering to solve跨-disciplinary problems that require both simulation-level rigor and production-grade robustness.
11 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Physics, GPA: 93/100, Rank: 3/33, Bachelor's degree, Physics, GPA: 93/100, Rank: 3/33 at Tsinghua UniversityDoctor of Philosophy (Ph.D.), Electrical and Computer Engineering, Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering at Princeton University
Chinese, English
Github Skills (13)
flutter10
e2e-test10
e2e-testing10
test-framework10
flutter-game10
dart10
performance-monitoring10
flutter-plugin10
flutter-apps10
integration-testing10
testing10
ios8
android8
Programming languages (22)
Github contributions (5)
flutter/plugins
Jun 2020 - Oct 2020
Plugins for Flutter maintained by the Flutter team
Role in this project:
Mobile Developer
Mobile DeveloperContributions:7 reviews, 8 commits, 16 PRs in 3 months
Contributions summary:Ming primarily worked on end-to-end (e2e) testing and integration testing for the Flutter plugins repository. They addressed issues related to device pixel ratio and added functionality for reporting extra information within the tests. Furthermore, the user integrated a performance monitoring system to measure frame build and rasterization times. These contributions indicate a focus on improving the reliability and performance of Flutter plugin tests.
dartandroidpluginflutter-pluginios
wuxiaoyang/Python-Challenge
Jul 2015 - Sep 2020
This repository contains solutions of Python Challenges.
Contributions:2 PRs in 5 years 2 months
pythonpython3
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