Tu Jinhui
Senior Software Engineer at Tencent
China
Summary
🤩
Rockstar🎓
Top SchoolTu Jinhui is a Senior Software Engineer based in China with six years of hands-on experience building reliable back-end systems and DevOps tooling at major firms including Tencent, Microsoft, and China Construction Bank. With a Master’s in Artificial Intelligence from Peking University and a bachelor’s in Automation, he brings strong academic grounding to practical engineering problems. He has contributed to the industrial-grade federated learning project FATE, focusing on cache fixes, database model refactors, and secure RSA integrations—work that reflects both deep system understanding and attention to data integrity. At Tencent he continues to apply this blend of backend, database, and infrastructure skills to scale production services. Known for pragmatic refactors and thoughtful parameter-level changes, he tends to favor sustainable, low-risk improvements that yield measurable reliability gains.
6 years of coding experience
3 years of employment as a software developer
Bachelor of Engineering, Automation, Bachelor of Engineering, Automation at Nankai UniversityMaster of Science, Artificial Intelligence, Master of Science, Artificial Intelligence at Peking University
Github Skills (11)
caching10
python10
rsa10
mysql9
database-design9
federated-learning9
machine-learning8
algorithm8
api-design7
apim7
api7
Programming languages (3)
Github contributions (5)
FederatedAI/FATE
Oct 2019 - Sep 2020
An Industrial Grade Federated Learning Framework
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:53 commits, 5 PRs, 60 pushes in 10 months
Contributions summary:Tu primarily focused on fixing cache bugs and refactoring database models within the federated learning framework. Their contributions included changes to database models, specifically converting data types, and improvements to caching utilities. They also demonstrated a strong understanding of the system's architecture by integrating RSA components and making modifications to function parameters.
industrialfederated-learning-frameworkmachine-learninggradefate
FederatedAI/FATE-Serving
Nov 2019 - Aug 2020
A scalable, high-performance serving system for federated learning models
Contributions:4 releases, 51 commits, 5 PRs in 9 months
pytorchscalablemonitorservingdeep-learning
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