I am a final-year PhD student in Computer Science at University of Wisconsin-Madison, where I am fortunate to be advised by Frederic Sala. Before that, I was a master’s student at Seoul National University, where I was lucky to learn deep learning, exploratory data analysis, and information theory from Wonjong Rhee. Prior to that, I received B.A in Psychology and B.S. in Computer Science and Engineering from Seoul National University.

My research focuses on data-centric AI, particularly programmatic weak supervision and weak-to-strong generalization in foundation models. These approaches use weaker models as supervision sources to train stronger models, providing labels, reward signals, and verification signals that guide more capable systems. I have also explored inference-time steering, which involves intervening on internal representations to improve robustness, alignment, and personalization of foundation models at inference time without fine-tuning.

Looking ahead, my vision is to develop strategies for supervising superhuman-level intelligence, where traditional human oversight is no longer sufficient. My research currently focuses on two directions. The first is weak-to-strong generalization, where weaker models are used as supervision sources to train stronger ones, providing labels, reward signals, and verification for more capable systems. The second is out-of-distribution (OOD) generalization, including challenges such as easy-to-hard generalization, length generalization, and compositional generalization.