Hwanjun Song
Assistant Professor at KAIST
Daejeon Metropolitan Area South Korea
Summary
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Senior🎓
Top SchoolHwanjun Song is an Assistant Professor at KAIST and a machine learning researcher with eight years of experience focused on AI-human value alignment and generative AI. Prior to academia he was a research scientist at AWS and NAVER, where he worked on large language models, abstractive summarization, automated evaluation, and transformer-based robustness and efficiency for real-world vision tasks. His industry roles are complemented by a PhD in Data Science from KAIST and a research internship at Google on RGB-D detection, reflecting a strong bridge between foundational vision research and applied LLM systems. He has a track record of translating research into deployable tools for evaluation and summarization, and his lab pursues alignment questions that sit at the intersection of ML, human-computer interaction, and ethics. Based in Daejeon, South Korea, he combines academic rigor with production-minded research experience across major global tech organizations. Colleagues describe him as someone who brings both deep technical breadth and a pragmatic focus on real-world impact.
8 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD Data Science, Doctor of Philosophy - PhD Data Science at Korea Advanced Institute of Science and Technology
Korean, English
Github Skills (27)
hierarchical10
mscoco10
responsive10
github-pages10
jekyll10
jekyll-theme10
backbone10
imagenet9
semantic-segmentation9
visual-recognition9
object-detection8
image-classification8
pytorch7
mask-rcnn7
swin-transformer7
Programming languages (3)
Github contributions (5)
songhwanjun/Co-teaching
Jan 2019 - May 2019
Contributions:79 commits, 62 pushes in 3 months
songhwanjun/songhwanjun.github.io
Jun 2018 - Jan 2020
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Contributions:275 pushes in 1 year 8 months
templategithub-pages-templatemmistakesmistakesgitbook
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