I’m a master’s student in Mathematical Data Science at Korea University, with a strong interest in applying computer vision techniques to practical, real-world challenges. My work focuses on developing models that can effectively interpret and utilize visual information in both industrial and medical contexts.

I’ve contributed to a range of projects, from vision-language modeling and image-based prediction to recommendation systems. These experiences deepened my interest in multimodal learning and robust model design. During my internship at the medical AI company CONNECTEVE, I worked on developing an AI-powered spinal diagnostic tool and contributed to a research publication based on the project. This experience gave me valuable insight into the practical challenges of applying AI in clinical settings, from model development to validation and real-world deployment.

I’m especially interested in building AI systems that aren’t just accurate, but also intuitive and genuinely useful in practice. I enjoy thinking about how models can support meaningful decisions—whether in healthcare, industry, or wherever they can make a positive impact.