Chia-hung Tai
Sr. Software Engineer at Mozilla Taiwan
Taipei, Taiwan
Summary
🤩
Rockstar🎓
Top SchoolChia-hung Tai is a senior software engineer based in Taipei with 12 years of experience building high-performance, production-ready systems across mobile, embedded, and backend domains. At Mozilla Taiwan he led the FoxEye project, delivering a 30x performance improvement for 720p camera processing on Firefox mobile and shipping real-time face detection demos in pure JavaScript. His background spans OS and platform work at HTC, RF calibration tools at Qisda, and NLP research at Academia Sinica, giving him a strong mix of systems, signal processing, and machine learning experience. An open-source-minded engineer, he contributes maintenance and data-processing fixes to notable projects like Microsoft’s Qlib, reflecting a focus on code quality and reproducible AI tooling. He combines academic rigor from a Master’s in MIS with practical systems optimization skills and a penchant for parallel computing and real-time image processing.
12 years of coding experience
8 years of employment as a software developer
Bachelor, MS, Bachelor, MS at National Chiao Tung UniversityMaster, MIS, Master, MIS at National Sun Yat-Sen University
Chinese, English
Github Skills (6)
python10
quantitative-finance10
algorithmic-trading9
finance7
machine-learning7
data-engineering6
Programming languages (3)
Github contributions (5)
microsoft/qlib
Dec 2021 - Dec 2022
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
Role in this project:
Backend Developer
Backend DeveloperContributions:17 reviews, 26 commits, 53 PRs in 11 months
Contributions summary:Chia-hung primarily contributed to code improvements and bug fixes within the Qlib repository, which is an AI-oriented quantitative investment platform. Their contributions included fixing typos, updating file encodings, and correcting file paths within the codebase. The user also addressed warnings and formatting issues in configuration and logging files, indicating a focus on code quality and maintainability. Additionally, the user made changes related to data collection and processing.
auto-quantpythoninvestment-strategiesempowerquant
ChiahungTai/czsc
Mar 2022 - Dec 2023
缠中说禅技术分析工具；缠论；股票；期货；Quant；量化交易
Contributions:59 pushes in 1 year 10 months
pythontradingdata-meshquantctp
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