Yunhak Oh

Ph.D. candidate in Data Science

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I’m passionate about using machine learning to solve complex scientific puzzles, bridging the gap between cutting-edge research and real-world impact.

This passion was forged during my time at NielsenIQ, where I grew from a Data Scientist to a Manager. There, I learned firsthand how to build practical, data-driven solutions, leading projects that enhanced operational efficiency and delivered significant business value, including one that cut costs by $54K USD.

To tackle even deeper challenges, I am now a Ph.D. candidate in the Graduate School of Data Science at KAIST, advised by Prof. Chanyoung Park. My research focuses on the intersection of Graph Representation Learning and its applications to biology, and I’ve been fortunate to publish my work in top-tier conferences like NeurIPS and ICML.

My goal is to continue creating practical value by applying advanced ML to meaningful scientific problems.

My Core Research Interests:

  • AI4Science - Biology
  • Graph Representation Learning
  • Recommender System

News

Sep 25, 2026 Two papers got accepted at NeurIPS 2026.
  • scTrilemma: Balancing Identity, Invariance, and Reconstruction in Single-Cell Representation Learning
  • Screening Lipid Nanoparticles through Structure-Ratio Alignment
Aug 17, 2026 Serving on the organizing committee for MM4SciReal: Multimodal AI for Science and the Real World at ACCV 2026.
  • Date: December 15, 2026 (Full-day)
  • Venue: Room 1001, Osaka International Convention Center (Grand Cube Osaka), Osaka, Japan
May 1, 2026 A paper got accepted at ICML 2026.
Nov 25, 2025 I started a research internship at HITS in Seoul. I am working on Single-cell Foundation Models for the Virtual Cell project within the AI Research Team.
Sep 19, 2025 A paper got accepted at NeurIPS 2025 as a spotlight presentation (Top 3.18 %).