Hello! I'm Hoonick.

I am an integrated M.S./Ph.D. student in Computer Science and Engineering at Korea University and a member of the Data Mining and Information Systems (DMIS) Lab, advised by Prof. Jaewoo Kang.

My research focuses on natural language processing and large language model systems for biomedical and clinical applications. I am particularly interested in developing reliable NLP systems that can reason over biomedical text, structured clinical data, and domain-specific knowledge to support scientific discovery and clinical decision-making.

Before concentrating on biomedical NLP, I explored how language technologies can be adapted to a range of specialized domains. My previous work includes food computing and cross-cultural cuisine reasoning, phishing and scam detection, natural-language-to-SQL generation over electronic health records, and biomedical question answering. I was part of the KU-DMIS team that participated in the EHRSQL 2024 shared task and the team that achieved first place overall in BioASQ 13b Phase B. I have also contributed to an LLM-based chain-of-response system for detecting and responding to online scams.

My academic background spans health science, neuroscience, and computer science. At Korea University, I completed a dual-degree curriculum in Health and Environmental Science, with an emphasis on radiological science, and Computer Science and Engineering, together with an interdisciplinary major in Brain and Cognitive Sciences. This multidisciplinary training shapes my interest in building computational systems that connect language, biomedical knowledge, and real-world health data.

Ultimately, I aim to develop biomedical AI systems that are not only technically capable, but also scientifically grounded, interpretable, and useful in practice.