Joongi Kim
CTO at Tatter Network Foundation
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolJoongi Kim is a CTO and research-oriented systems engineer with 20 years of experience building high-performance backend systems, heterogeneous accelerator support, and production-grade networking (GPU/Xeon Phi, Intel DPDK, custom Linux drivers). He blends deep systems programming with full‑stack fluency—Python asyncio and modern JavaScript—while leading Lablup to advance research and education via containerized compute platforms like Backend.AI. An active open-source practitioner, he has contributed to core projects including CPython (asyncio/contextlib fixes) and aiohttp, improving async behavior and WebSocket reliability. His background combines industrial research (Microsoft cloud analysis), academic rigor (PhD-level CS at KAIST), and long-term community stewardship in projects such as Textcube and CCIU, reflecting a rare mix of low‑level performance tuning and developer-facing tooling.
20 years of coding experience
KTH Royal Institute of TechnologyDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Korea Advanced Institute of Science and Technology
Korean, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (23)
asynchronous10
dependency-management10
context-manager10
python10
async10
setuptools10
http10
websocket10
asyncio10
websockets-client10
websocket-client10
client-websocket10
documentation10
aiohttp10
testing9
Programming languages (25)
Github contributions (5)
lablup/backend.ai
Oct 2016 - Jan 2023
Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, TPU, IPU and other NPUs.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:12 releases, 1071 reviews, 848 commits in 6 years 4 months
Contributions summary:Joongi contributed to the package structure and development of the "sorna" package, which is associated with the "backend.ai" project. They excluded a subpackage from the build, indicating a focus on streamlining the project. The user added and modified files related to documentation and configuration (e.g., setup.py and docs files). The work suggests that the user is focused on the project's build, documentation, and organizational aspects.
diversepythonpluggablebackendaicloud-computing
ragulpr/wtte-rnn
Jul 2017 - Jul 2017
WTTE-RNN a framework for churn and time to event prediction
Role in this project:Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:18 commits, 17 pushes in 18 days
Contributions summary:Joongi primarily focused on improving the project's build and deployment process, alongside updating core dependencies. They updated the `setup.py` file to manage dependencies, include sub-packages, and enable compatibility across Python versions. The user also addressed code style issues, removed unused imports, and updated documentation-related dependencies. Furthermore, they incorporated the use of the `six` library for Python 2/3 compatibility.
rnnpredictiontime-to-eventdeep-learningchurn
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.