Jiun Bae
Research Engineer at Return Zero
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolJiun Bae is a research engineer based in Seoul with 11 years of experience specializing in machine learning, computer vision, and natural language processing. He has driven production-ready research at companies like NCSOFT and NAVER, building PyTorch training frameworks, real-time facial animation systems, and scalable model deployment pipelines for digital humans. His work blends deep research—such as speech-driven 3D facial animation and depth estimation for 3D mapping—with practical engineering like preprocessing pipelines for high-fidelity motion capture. Jiun is also an active communicator of core ML concepts, contributing Korean translations and explanations to the CS231n course materials to broaden accessibility. He combines an academic foundation from Hanyang University with hands-on product impact, often bridging prototype research and internal tooling to accelerate team productivity. A detail that sets him apart is his track record of shipping both research innovations and developer-facing infrastructure that makes experimental models usable in production.
11 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Hanyang UniversityBachelor's degree, Computer Engineering, Bachelor's degree, Computer Engineering at Yonsei University
English, Korean
Stackoverflow
550reputation
92kreached
23answers
2questions
Github Skills (9)
machine-learning10
softmax10
data-science10
python9
whitespace6
dictionary6
double-quotes6
unicode6
list-comprehension6
Programming languages (10)
Github contributions (5)
aikorea/cs231n
Apr 2016 - Aug 2016
CS231n 번역 프로젝트
Role in this project:
Data Scientist
Data ScientistContributions:22 commits, 6 PRs, 16 comments in 3 months
Contributions summary:Jiun contributed to the CS231n 번역 프로젝트 by updating and translating various assignments. Their work focused on adapting and explaining concepts related to k-Nearest Neighbor (kNN), image features, and Softmax classifiers. They also modified documentation and translated the content for better understanding in Korean. This indicates a focus on understanding and communicating core machine learning concepts.
javacs231n
HYU-ICEWALL/Study-C
Mar 2016 - Feb 2017
Contributions:31 commits, 12 PRs, 6 pushes in 11 months
freshman
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