Zhangqian Liu
Software Engineer at Google
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolZhangqian Liu is a software engineer based in San Jose with eight years of experience building scalable web and distributed systems, currently at Google after contributing to Baidu’s Apollo autonomous driving simulation platform. He blends full-stack UI work—authoring Dreamview visualization and Dreamland cloud simulation—with backend improvements to high-profile open-source projects like Apollo, where he enhanced traffic light and map simulation accuracy. Trained in IT at Carnegie Mellon with a BS in Environmental Science from Fudan, he brings a data-driven research mindset that previously boosted air pollution modeling accuracy by over 50%. Quick to learn cutting-edge tools, he excels at turning complex simulations and large-scale scenario data into reliable developer-facing services that accelerate algorithm validation.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS Environmental Science, Bachelor of Science - BS Environmental Science at Fudan UniversityMaster's degree Information Technology, Master's degree Information Technology at Carnegie Mellon University
English, Chinese
Github Skills (7)
simulations10
simulation10
c-language10
cprogramming-language10
autonomous-driving10
apidoc7
api7
Programming languages (4)
Github contributions (5)
ApolloAuto/apollo
Oct 2018 - Sep 2019
An open autonomous driving platform
Role in this project:
Back-end Developer
Back-end DeveloperContributions:66 commits, 26 PRs, 3 pushes in 11 months
Contributions summary:Zhangqian primarily focused on improving the simulation aspects of the Apollo autonomous driving platform. They updated the traffic light heading calculations and corrected the calculation of traffic light boundaries. The user also modified the map service, updating the ID retrieval methods for various map elements such as signals and stop signs. These changes indicate a focus on improving the accuracy of the simulation environment for autonomous vehicle testing.
autonomousmachine-learningautonomyautonomous-drivingapollo
kiboliu/Jinri-Toutiao-News-Dig-and-Recommend-System
Nov 2017 - Jan 2018
Contributions:9 commits, 5 pushes, 2 branches in 2 months
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