Chen Fei
Quantitative Developer & Researcher
Shanghai, Shanghai, China
Summary
🤩
Rockstar🎓
Top SchoolChen Fei is a quantitative developer and researcher with 18 years of engineering experience, now based in Shanghai, who blends production-grade software engineering with hands-on quantitative research for multi-asset trading strategies. He has led teams building ETL, factor generation, backtesting and execution pipelines across CTA, A-share, European equities, crypto and options, and maintains mission-critical daily data archives and point-in-time financial ingestion. Technically fluent in Python, Pandas, MySQL and Airflow with a strong backend pedigree in Golang, Node.js and distributed systems, he has also contributed to high-profile open-source projects such as Microsoft’s LightGBM and cross-platform build tooling in xmake. His work is characterized by rigorous reproducibility and numerical precision—e.g., refactoring factor generation to ensure value-level consistency to 1e-10—while also delivering web-scale data collection via custom crawlers for alternative datasets. Colleagues rely on him for productionizing research into live trading systems and for clear risk and performance reporting across products.
18 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Shanghai Jiao Tong University
English
Github Skills (33)
c-language10
lib10
package-management10
crossbuild10
machine-learning10
xmake10
cmake10
networking10
lua10
data-loading10
build210
go10
package10
lightgbm10
toolchain10
Programming languages (15)
Github contributions (5)
shadowsocks/shadowsocks-go
Dec 2012 - Jun 2016
go port of shadowsocks (Deprecated)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:4 releases, 268 commits, 15 PRs in 3 years 6 months
Contributions summary:Chen primarily contributed to the core functionality of a Go-based implementation of shadowsocks. Their work involved converting data types, implementing encryption functions, and refactoring connection handling within the project. They also introduced improvements to the system by exposing a connection interface. The contributions collectively enhanced the secure proxy's usability and security.
golangshadowsocksproxy
microsoft/LightGBM
Dec 2020 - Nov 2021
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Role in this project:ML Engineer
ML EngineerContributions:55 reviews, 13 commits, 15 PRs in 11 months
Contributions summary:Chen primarily contributed to the codebase by implementing features related to data loading, configuration, and binary file handling within the LightGBM framework. They added a new task type, "save_binary", and ensured the consistency of data loading parameters. Additionally, the user addressed bug fixes, such as a typo, and incorporated precise text file parsing for enhanced data processing. These contributions improve the functionality and data handling capabilities of the machine learning library.
kagglepythondata-mininglightgbmmicrosoft
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