I am a software engineer at Digit Systems in Atlanta and an M.S. in Artificial Intelligence student at Columbia University.
I study and build AI systems and governance: the structures that allow increasingly capable agents to operate safely, accountably, and usefully in the real world. I like carrying an idea all the way through backend engineering, databases, automation, testing, and production operations.
At Digit Systems, I develop ERP and remote monitoring software for MRI and CT maintenance. My work connects Raspberry Pi and Linux deployment automation, Node.js and Python monitoring services, and Playwright end-to-end testing into systems that can be deployed and observed in the field.
I also built the HTP AI Reflection Platform, which has generated 3,000+ reports through a multimodal workflow built with Angular, Node.js, MariaDB, and OpenAI APIs. More than 80% of collected user feedback has been favorable.
What I explore
- AI systems and governance — authority, accountability, auditability, safety, and measurable value
- Production software for AI — backend systems, data, deployment automation, and software quality
- AI markets and future scenarios — how technical shifts may reshape industries, work, institutions, and public life
I earned a B.S. in Computer Science from the University of Wisconsin–Madison and previously served as a Telecommunications Operations Specialist in the Republic of Korea Air Force. Across these environments, I learned that a good system must do more than function: it must be deployable, observable, and accountable.
In the English edition, I publish selected field notes and project case studies. Each piece separates observable signals from interpretation and longer-range forecasts, so uncertainty remains visible rather than being disguised as certainty.