Daeeun (Dan) Kim · 김대은
I study what actually
happens between people
and AI — then I build it.
I study data science at Kwangwoon University, observe people in the field, and design the app that answers what I find. I distrust flattering numbers first — and retract my own findings when they don’t hold.
How I work
Observe, design, verify — and retract
Research is less about producing a conclusion than about checking whether it survives. So my work carries as many retracted numbers as successful ones.
- 01
Observe in the field
Not surveys — the moment of use. I have recorded what people actually do in 100+ shops, in army barracks, and on neighbourhood streets.
- 02
Write the hypothesis as a screen
An observation gets tested on a screen. Delayed replies, visible progress, explicit consent — each one is a question about whether behaviour changes.
- 03
Distrust my own conclusion
A 38-second dwell time was really 1.5 seconds — an artifact of background timeouts. Six metrics were retracted and the analysis re-run.
- 04
Record what I cannot explain
When an unexpected user population appeared, I wrote down that it was unexplained rather than inventing a reason. That becomes the next question.
Work
What building taught me
Each project starts as a question, and records the attempt to answer it with screens and data.
Writing
Publishing the numbers that failed
- 18 Nov 2025Bootcamp (UX Collective)
My Fake Door Test Got a 16.5% CTR… and a 2.47% Conversion Rate. Here's What I Learned.
The raw data from a three-pronged fake-door test, and an autopsy of why the clicks soared while sign-ups collapsed.
- Dec 2025Bootcamp (UX Collective)
I Killed My Darling (Again): How Legal Nightmares and Bored Users Forced a B2B Pivot
How two walls — legal constraints and bored users — pushed a B2C game into a B2B data business.
- May 2026Medium
The Three Desires Underneath Every Viral Comment
The three desires beneath the things people say when they predict a trend — and how to put them on a screen.
About
If I’m curious, I build it to find out
In secondary school I was listening to music and wondered which instrument was making which sound when several played at once. That single question turned into an instrument-classification algorithm — and it set how I treat technology: build the thing to find out.
The same habit had me counting the tactile paving in my district — 40% of it was failing — and, over two years inside a U.S. Army base, watching where foreigners get stuck paying for things in Korea. Now I watch how people and AI actually get along.
I build screens and I try to break my own conclusions. When a 38-second dwell time turned out to be 1.5 seconds, I retracted all six affected metrics instead of quietly correcting them. I don’t know another way for research to earn trust.
Education
- Kwangwoon UniversityMar 2023 – Present
B.S. in Data Science, School of Information Convergence
Two-year leave for military service; returning September 2026 as a second-year student
- Daejeon Daeshin High SchoolMar 2020 – Feb 2023
Daejeon, Republic of Korea
Press
- Naeil Education weekly2023
2023 Early-Admission Interview — Daeeun Kim, Software Talent track, Kwangwoon University School of Information Convergence
Print feature in the Korean education weekly Naeil Education, covering his secondary-school projects — an instrument-classification algorithm, scooter safety, and receipt-ink waste
- Naeil Education weekly2023
2023 Early-Admission Interview Series — Daeeun Kim, Kwangwoon University, School of Information Convergence
Admission interview series, covering how he prepared for the comprehensive-review interview
Contact
If the work needs someone to go and watch people, I’d like to talk.
A lab, a product team, an early startup — the shape doesn’t matter, so long as the screens are built on evidence from the field.