Sungmin Kang
Summary
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SeniorSungmin Kang is a machine learning researcher and engineer with a decade of hands-on experience, currently pursuing an MS at USC and researching uncertainty quantification and truthfulness in LLMs at the vITAL lab. He has designed communication-efficient and parameter-efficient federated/LLM training algorithms that cut communication by up to 83% and fine-tuned models by updating only 0.1% of parameters. His open-source work includes a library of 30 truth evaluation methods for language model generations and practical FL systems deployed on edge devices like Raspberry Pis. Comfortable bridging theory and systems, he has applied transfer learning to multimodal medical prediction and delivered lectures and projects on federated learning. Having served as a sergeant in the ROK Army, he brings disciplined leadership to collaborative research teams in Los Angeles.
10 years of coding experience
Github Skills (11)
replication5
large-language-models4
java3
llm2
python2
deep-reinforcement-learning2
machine-learning1
javaparser1
language-model1
posters1
image-processing1
Programming languages (4)
Github contributions (5)
priv-purpose/evolving-NN-code
Oct 2018 - Dec 2018
Contributions:48 commits, 32 pushes, 1 branch in 1 month
smkang96/defects4j-repair
Jan 2022 - Sep 2022
Open-science repo for our experimental results of automatic software repair on the Defects4J benchmark of Java bugs
Contributions:1 push, 456 branches in 8 months
java
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