Yunhak Oh

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