Research
Research Interests
I believe the most impactful AI research happens at the boundary between technology and human experience. My work is driven by a simple question: how do we build intelligent systems that genuinely help people — not just in controlled lab settings, but in the messy, unpredictable flow of everyday life?
Focus Areas
Human-Agent Interaction
Designing and evaluating AI agents that collaborate naturally with humans. My work explores how LLM-powered agents can support skill learning, decision-making, and daily tasks — with a focus on trust, transparency, and appropriate autonomy.
Context-Aware AI Systems
Building AI systems that understand and adapt to the user's context — physical, cognitive, and situational. This includes personalized feedback systems, health monitoring via voice and multimodal signals, and adaptive interfaces that respond to real-world conditions.
LLM-Integrated Applications
Developing production-grade systems that integrate large language models into human workflows. From RAG pipelines and fine-tuning strategies to evaluation frameworks, I focus on making LLMs reliable, explainable, and genuinely useful in real-world contexts.
Current Position
M.S. Candidate — Human-Centered Intelligent System Lab
GIST (Gwangju Institute of Science and Technology) · Mar. 2025 – Present
Advisor: Prof. SeungJun Kim
Background & Motivation
My journey started in software engineering — building products at a startup, competing in hackathons, and learning what it means to ship real software to real users. That grounding keeps me focused on practicality: research should ultimately be deployable.
Through internships at SNUBH Medical AI Center and GroupByHR, I saw firsthand how AI could either empower or frustrate people depending on how thoughtfully it was designed. Those experiences shaped my conviction that HCI and AI belong together.
Today, I design and study AI systems through the lens of the people who use them — asking not just “does this work?” but “does this help, and why?”