Daniel Lee
Graduate Research Assistant
San Jose, California, United States
Summary
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Senior🎓
Top SchoolDaniel Lee is a graduate research assistant and MS candidate in Software Engineering at San José State University with eight years of hands-on experience in software and applied machine learning. He specializes in neural signal analysis and deep neural network modeling for action prediction using real patient brain recordings, pairing rigorous data preprocessing with model optimization and reproducible pipelines. Previously he interned on emotion-classification workflows for Google Cloud Video Intelligence, performing feature engineering and training ML models on large multimedia datasets. Based in San Jose, Daniel is pursuing an entry-level software engineering role where he can blend his research-grade ML experience with practical software development for product-focused teams. A detail-oriented engineer, he brings both academic rigor and production-minded implementation—often surfacing subtle preprocessing gains that materially improve model performance.
8 years of coding experience
Master of Science - MS Software Engineering, Master of Science - MS Software Engineering at San José State University
Korean, EnglishProgramming languages (2)
Github contributions (5)
JimSongTheGreatest/Kocoon
Jul 2022 - Aug 2022
Contributions:14 commits in 29 days
daniellee97/CMPE133-SJSUSRAC
Sep 2019 - Dec 2019
Contributions:2 PRs, 19 pushes, 3 branches in 3 months
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