Yunfei He is an Applied Science Manager at Amazon with 7 years of experience building ML, causal inference, and optimization solutions that monetize selling partner services and inform fee strategy worldwide. He combines a strong operations research background from Penn State and industry experience in revenue management at airlines and cruise lines with hands-on software engineering—contributing to major open-source projects like Vite, rust-analyzer, webpack and the Rust-based swc and rspack toolchains. Equally comfortable in Python, Rust, and production ML stacks, he bridges research and engineering to ship robust code-generation, bundling, and IDE features. Known for pragmatic experimentation and improving system calibration at scale, he also brings a developer’s curiosity—self-described “programmer by interest”—to performance-sensitive backend and frontend tooling.
7 years of coding experience
Bachelor Logistics Engineering, Bachelor Logistics Engineering at Tongji University
Master of Science (MS) Industrial Engineering and Operation Research, Master of Science (MS) Industrial Engineering and Operation Research at Penn State University
The fast Rust-based web bundler with webpack-compatible API 🦀️
Role in this project:
Back-end Developer
Contributions:2 releases, 521 reviews, 271 PRs in 1 year 1 month
Contributions summary:Yunfei's commits focus on adding assertions, sorting modules, and handling errors within the `rspack` project. The changes indicate involvement in core functionality related to module resolving, compilation, and code generation within the Rust-based web bundler. The contributions demonstrate a focus on improving the stability, efficiency and code quality of the bundler.
Contributions:3 reviews, 1 PR, 6 comments in 3 years 4 months
Contributions summary:Yunfei primarily contributes to the `rust-analyzer` project by implementing and refining features related to code completion and diagnostics. They focus on enhancing the IDE's ability to provide suggestions, specifically for `async` functions within traits. The user also addresses and reverts a diagnostic error message issue and incorporates unit tests for completion features. In addition, the user applies code formatting changes.
rustlsp-servercompileridefront-end
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