Research
Information extraction, privacy-aware LLM systems, and human-centered evaluation frameworks.
Publications
Peer-reviewed papers on privacy-preserving LLM APIs, checklist-based evaluation, and efficient reasoning.
I am a Ph.D. candidate in Industrial Engineering at Seoul National University, advised by Prof. Pilsung Kang in the Data Science and Business Analytics Lab. My current work centers on text embedders, LLM reasoning, and solving practical challenges that arise when bringing large language models into production settings.
My broader interests include:
- Developing models that can unify NLU and NLG tasks
- Trustworthy LLM evaluation frameworks that are easy to build and maintain
- Efficient learning strategies for scalable LLM reasoning
I enjoy collaborating with multidisciplinary teams to turn research prototypes into practical tools. Feel free to reach out if you are interested in working together.
I also co-organize an NLP paper review study group called Unknown NLP. We publish our session write-ups publicly at unknown-nlp.github.io so that other researchers and practitioners can follow along and join the discussion.
An expanded English write-up for this section is coming soon.