About
About
I am a master's candidate at Seoul National University working on urban data, sensing, and computational ways of studying the lived city.
Background
I studied Urban Planning & Engineering at Yonsei University, with a double major in Interior Architecture. I wanted to look at cities at a finer spatial scale, so I moved to the Department of Architecture & Architectural Engineering at Seoul National University for my master’s. Now I’m hoping to mix those scales in my own research.
My work has moved from statistical handling of incomplete spatial datasets toward applications that combine urban research with computer vision and sensing-oriented methods. That trajectory is visible across the floor area ratio imputation paper and the vacant-housing grade audit.
Current interests
These are rough ideas at the moment, each parked in a short note:
- Where urban datasets disagree
- Were demolished buildings different from the start?
- Re-running urban planning studies with agents
- What makes a floor plan AI-readable?
Tools I use
- Python, R, Q-GIS, and PostgreSQL
- Machine learning and computer vision
- AI-based workflows (Grasshopper design automation, Markdown knowledge bases)
Public links
- CV PDF
- LinkedIn: dongjoon-park
- GitHub: github.com/gbjun7333