I am a machine learning researcher at AITRICS, a healthcare AI startup in Korea, where I am advised by Prof. Eunho Yang and Prof. Juho Lee. I also collaborate closely with Prof. Evan Shelhamer at The University of British Columbia. I completed my Master’s degree in Artificial Intelligence at KAIST under Prof. Eunho Yang and hold a Bachelor’s degree in Computer Science and Mathematics from KAIST.

I am open to research collaborations globally and intend to pursue doctoral studies beginning Fall 2026. Should my research interests align with your work, I would be pleased to discuss potential collaborations.

Research Interests:

• Trustworthy Machine Learning
• Deep Generative Models
• Machine Learning Theory

My ultimate research goal is to design trustworthy machine learning algorithms that enable stable deployment in real-world applications, with a particular focus on deep generative models. I work toward this goal by developing empirically well-motivated and theoretically grounded methods, complemented by rigorous analysis rooted in machine learning theory.

In this pursuit, I have addressed key challenges in trustworthy machine learning, including out-of-distribution generalization, explainable artificial intelligence, and uncertainty calibration, across diverse modalities such as vision, vision-language, speech, tabular data, and time series.