Kwon Ko
Research Assistant at Stanford University
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolKwon Ko is a research-focused software engineer and PhD student in Computer Science at Stanford with eight years of hands-on experience building AI-infused systems spanning HCI, generative models, and applied alignment. Currently a Research Assistant in the Druckmann Lab working on human speech BCI, he has prior research and industry experience at Microsoft Research, NAVER WEBTOON, KAIST, and the University of Michigan where he led projects on text-to-image tools, synthetic NL dataset generation, and constitutional AI for community norms. As the first and only engineer at SkillBench he designed and shipped a full‑stack AI agent task-management web app that he successfully pitched to OpenAI and BP, demonstrating product sensibility alongside technical depth. His work consistently bridges prototyping and publication—several projects led at KAIST and NAVER resulted in peer-reviewed outputs and deployed systems for creative collaboration and content moderation. Fluent in both rigorous experimentation and end-to-end engineering, he pairs a mathematics and physics undergraduate foundation with multidisciplinary research to tackle practical AI+HCI problems. Notably, his background includes operational discipline from military service, which he leverages in coordinating complex, cross-institutional research efforts.
8 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Computer Science and Engineering, Master of Science - MS, Computer Science and Engineering at Seoul National UniversityBachelor of Science - BS, Mathematics, Bachelor of Science - BS, Mathematics at Hanyang UniversityBachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at Konkuk UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Stanford University
Github Skills (71)
projection10
topological-data-analysis10
approximation10
dimensionality-reduction10
uniform10
scene-text9
rosetta9
high-resolution9
stylegan9
ocr-recognition9
image-synthesis9
visualization9
text-recognition9
manifold9
ieee9
Programming languages (7)
Github contributions (5)
hyungkwonko/umato
Jun 2021 - Jul 2022
Uniform Manifold Approximation with Two-phase Optimization (IEEE VIS 2022 short)
Contributions:4 commits, 3 PRs, 195 pushes in 1 year 1 month
dimensionality-reductionoptimizationumatoshorttopological-data-analysis
hyungkwonko/CV
Jan 2019 - Sep 2024
Contributions:49 pushes, 1 branch in 5 years 9 months
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