Sungmin Kang
Graduate Student Researcher
Los Angeles, California, United States
Summary
👤
Senior🎓
Top SchoolSungmin 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
1 year of employment as a software developer
Master of Science - MS, Electrical and Computer Engineering (Machine Learning and Data Science), Master of Science - MS, Electrical and Computer Engineering (Machine Learning and Data Science) at University of Southern CaliforniaBachelor of Science - BS, Electronic Engineering, Bachelor of Science - BS, Electronic Engineering at 서강대학교
Github Skills (11)
terrain4
repair3
java2
science2
benchmark2
reinforcement-learning2
deep-reinforcement-learning2
open-science1
machine-learning1
posters1
image-processing1
Programming languages (3)
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
sciencebenchmarkdefects4jopen-sciencerepair
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