Jang-hyun Kim
Machine Learning Researcher at Apple
Seoul, United States
Summary
👤
Senior🎓
Top SchoolJang-hyun Kim is a machine learning researcher with 8 years of experience, currently working on foundation models at Apple after leading LLM inference-efficiency research as a freelance AI researcher for NAVER Cloud. His work centers on meta-optimization techniques that let trained networks compress datasets and contexts, guide augmentation via saliency, and automatically surface problematic data—reducing reliance on manual curation. He holds a PhD in Computer Science from Seoul National University and has applied deep models to causal discovery in human genes during a visiting scholar stint at NYU. Notably, he led the FastKVZip project on large-scale LLM inference efficiency and has prior industry experience in speech enhancement and applied ad analytics. Based in Seoul with international research exposure, he combines theoretical rigor with practical system-focused contributions that speed training and inference.
9 years of coding experience
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Seoul National UniversitySeoul Science High School
English
Github Skills (30)
language-model10
speaker-verification10
compression10
data-augmentation10
transformers9
pytorch9
llm9
llm-inference9
python9
large-language-models9
inference9
parameterization9
statistics9
robustness9
synthetic-data9
Programming languages (2)
Github contributions (5)
Janghyun1230/Janghyun1230.github.io
Mar 2019 - Feb 2026
Contributions:307 pushes, 1 branch in 7 years
snu-mllab/Efficient-Dataset-Condensation
May 2022 - Jul 2022
Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)
Contributions:79 commits, 27 pushes, 8 comments in 2 months
parameterizationpytorchsynthetic-datadataset-condensationdataset-distillation
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