Jung Song
AI Research Engineer at NAVER WEBTOON
Seongnam-si, South Korea
Summary
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Senior🎓
Top SchoolJung Song is an AI research engineer with 11 years of experience specializing in computer vision and content security, currently building harmful content detection systems at NAVER WEBTOON. With a master's from Seoul National University and a strong track record at TmaxData leading anomaly detection, super-resolution, 3D point cloud segmentation, and face recognition projects, he bridges applied research and production-ready ML solutions. He has hands-on experience shipping lightweight models and demos (TensorFlow/PyTorch, TFjs, Flask, TRITON) and supervising cross-domain projects from industrial defect detection to skin/scalp diagnosis. Known for combining transfer and weakly supervised learning techniques, he often tackles data-scarce problems and domain adaptation challenges. Fluent in both vision and NLP approaches, he brings a practical researcher’s mindset to content safety at scale.
11 years of coding experience
3 years of employment as a software developer
Master's degree, Digital Contents and Information Studies, 학점 4.03/4.3, Master's degree, Digital Contents and Information Studies, 학점 4.03/4.3 at Seoul National UniversityHigh School Diploma, Japanese Language and Literature, High School Diploma, Japanese Language and Literature at Gwacheon Foreign Language High School학사, Computer Software/Media Application, 4.02, 학사, Computer Software/Media Application, 4.02 at 아주대학교
Korean, English, JapaneseGithub contributions (5)
jwsong0617/Sensor-Making
Jul 2015 - Aug 2015
Contributions:119 commits, 125 pushes, 1 branch in 19 days
jwsong0617/mediaProject
May 2016 - May 2016
Contributions:5 commits, 5 pushes, 1 branch in 10 days
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