Chih-chieh Yang
Research Staff Member at IBM
Town of Yorktown, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolChih-chieh Yang is a Research Staff Member at IBM with a decade of experience building and optimizing parallel programming models and next-generation software systems for cloud and HPC environments. He focuses on performance and scalability of cloud control planes and distributed machine learning, bridging research and practical engineering to scale workloads to supercomputers and future extreme-scale systems. His background spans academia and industry—PhD in Parallel Computing from UIUC, postdoc and research roles, plus early embedded and SoC experience at MediaTek and NVIDIA internships—giving him a rare blend of systems, firmware, and runtime expertise. He contributes to high-profile open-source projects like Kubernetes, where he’s improved integration tests and validated concurrency isolation and metrics for API server flow control. Colleagues rely on him for diagnosing subtle concurrency and metrics issues that reveal architectural bottlenecks, and he often pairs intelligent simulation with empirical measurement to drive solutions. Based in Yorktown, NY, he combines deep technical rigor with a pragmatic drive to make complex distributed systems more reliable and scalable.
10 years of coding experience
10 years of employment as a software developer
University of Illinois Urbana-ChampaignB.S., Computer Science, B.S., Computer Science at National Tsing Hua University
English, Chinese, French
Github Skills (7)
kubernetes10
go10
prometheus10
kubernetes-pods10
testing10
apidoc9
api9
Programming languages (8)
Github contributions (5)
kubernetes/kubernetes
Jul 2022 - Aug 2022
Production-Grade Container Scheduling and Management
Role in this project:
Backend & QA Engineer
Backend & QA EngineerContributions:17 reviews, 10 commits, 26 comments in 26 days
Contributions summary:Chih-chieh primarily worked on integration tests within the Kubernetes project, focusing on the flowcontrol component. Their contributions involved writing and refactoring test code to ensure the correct behavior of concurrency isolation features. They fixed metrics retrieval issues, added new test cases, and refined existing tests for improved accuracy and maintainability. The user demonstrated expertise in testing the interaction between API server flow control and priority levels, using prometheus metrics for validation.
containersschedulingdockergradeproduction-grade
cyang49/vllm
Jun 2024 - Apr 2025
A high-throughput and memory-efficient inference and serving engine for LLMs
Contributions:1 PR, 36 pushes, 8 branches in 9 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.