Lufan Zhao
Software Engineer at Xiaomi Technology
Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolLufan Zhao is a pragmatic software engineer with 12 years of experience building backend systems, AI platform tooling, and deployment infrastructure at companies like ByteDance, ZTE, and currently Xiaomi. He is passionate about code quality—treating compiler warnings as errors and leveraging testing, static analysis, and CI to keep projects robust. Lufan contributes actively to open source, including improvements to notable projects such as mozilla/grcov and Microsoft VSCode, where he focuses on cross-platform correctness and maintainability. His background spans distributed training and deployment systems as well as networking device configuration, giving him a strong systems-oriented perspective. Outside work he routinely sharpens skills through personal projects and rigorous tooling practices, reflecting a practical commitment to craftsmanship.
12 years of coding experience
9 years of employment as a software developer
Bachelor's degree Software Engineering, Bachelor's degree Software Engineering at Tianjin Normal UniversityMaster's degree Computer Technology, Master's degree Computer Technology at Tianjin University of Technology
Chinese, English
Stackoverflow
2,387reputation
190kreached
10answers
56questions
Github Skills (13)
code-optimization10
rust10
code-formatting9
build-tools9
command-line-tool8
file-operations7
fileio7
filesystem7
windows6
winforms6
fonts6
winapi6
treeview6
Programming languages (22)
Github contributions (5)
mozilla/grcov
May 2021 - May 2021
Rust tool to collect and aggregate code coverage data for multiple source files
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 commits, 2 PRs, 1 comment in 4 days
Contributions summary:Lufan primarily focused on improving the `grcov` tool's functionality and code quality. Their contributions involved refactoring the codebase by replacing string types with `OsStr` for improved platform compatibility and avoiding `unwrap()` calls. They addressed Clippy warnings, formatted code for better readability, and optimized the code by reducing redundant function calls.
code-coveragerust
Adlik/Adlik
Sep 2019 - Dec 2020
Adlik: Toolkit for Accelerating Deep Learning Inference
Contributions:9 reviews, 115 commits, 129 PRs in 1 year 2 months
deep-learninginferencetensorflow-servingopenvinotensorrt
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