Summary
Sukwon Yun is a research-focused AI engineer and PhD student at UNC Chapel Hill with five years of experience applying graph neural networks and recommender systems to real-world problems. Currently a research intern at Genentech in Regev Lab, he blends computational biology interests with a strong graph ML background gained through research roles at Tokyo Institute of Technology, KAIST, and Hanyang University. His work spans graph convolutional networks, graph embedding, and neural graph collaborative filtering, often tackling missing-feature scenarios and scalable recommendation models. Based in Seattle, he maintains a public portfolio at sukwonyun.github.io that reflects both academic rigor and practical experimentation. Notably, his trajectory bridges industrial engineering foundations with cutting-edge AI-for-biology research, positioning him to translate graph ML advances into biological insights.
5 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Industrial Engineering, Bachelor of Science - BS, Industrial Engineering at 한양대학교
Master's degree, Industrial and Systems Engineering, Master's degree, Industrial and Systems Engineering at 한국과학기술원(KAIST)
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of North Carolina at Chapel Hill