About Me
I am a Ph.D. candidate in Artificial Intelligence at the Theory of Computation (ToC) Lab, Yonsei University, advised by Prof. Yo-Sub Han. My research focuses on enhancing the safety and transparency of large language models (LLMs) through detection and attribution techniques. In particular, I explore two complementary approaches: linguistic/stylistic feature-based detection, which analyzes differences in writing patterns between human- and LLM-generated text/code; and LLM watermarking, which embeds imperceptible signals into generated outputs. I have developed detection and watermarking systems that generalize across multiple modalities (natural language and code) and languages (including English, Korean, Python, C, C++, and Java). I am deeply interested in AI safety, responsible AI, and the development of interpretable systems for trustworthy AI.
Research Interests
- Detection of LLM-generated text/code using linguistic/stylistic features
- LLM watermarking for LLM-generated text/code attribution and provenance
- Korean natural language processing
- Code AI
Recent News
- [Sep 2025] Paper accepted to Engineering Applications of Artificial Intelligence.
- [Aug 2025] Two papers accepted to EMNLP 2025.
- [Aug 2025] Presented KatFishNet at ACL 2025 (Main) in Vienna, Austria.
- [July 2025] Paper accepted to Expert Systems with Applications.
- [March 2025] Paper accepted to Engineering Applications of Artificial Intelligence.