About
Founder & CEO, Doogooda · Harvard PhD · Former faculty (Operations/Tech)
I'm building Doogooda — auditable decision systems for hospital operations and public institutions.
Doogooda operates two products: Entity Flow for US hospital operations and Entity Value for Korean government and institutional clients. Both turn operational data into auditable decision packets—evidence, constraints, trade-offs, and decision logs—so institutions can approve actions, not "AI recommendations."
Currently: Based in Madison, WI through gener8tor's gBETA Healthcare accelerator, working directly with American hospitals on operational decision-making through Entity Flow—bridging what I've built in Korea's universal healthcare system with the US market.
Method: Causal inference → scenario simulation → constrained optimization → auditable decision artifacts.
Focus Areas
Healthcare Operations
Clinical operations as policy-native decision intelligence. Entity Flow (US) helps hospitals structure staffing, capacity, and resource decisions with auditable logic. Entity Value (KR) serves government institutions with data-driven evaluation frameworks.
Decision Systems
Frameworks for structuring choices under uncertainty—trade-offs, constraints, and governance. This is the methodological foundation that both Entity Flow and Entity Value are built on.
AI Governance
Auditable AI for real institutions. Moving beyond explainability to accountability—because in regulated environments, "the model got it wrong" isn't a defensible answer.
Credentials & Affiliations
How I Build
Evidence-first
When I advised on hospital staffing decisions, the first deliverable wasn't a recommendation—it was a table showing what we knew, what we assumed, and what would need to change to flip the decision. This is how Entity Flow works: evidence before action.
Trade-offs, not "best options"
I don't hand over a single recommendation. Entity Flow presents three options with explicit trade-offs: this one saves money but increases wait times; this one is cost-neutral but reduces overtime. The institution decides.
Decision memos
Every decision has a paper trail—assumptions, constraints, scenarios considered, what was chosen and why. In regulated environments, "we thought it was best" isn't a defensible answer. This auditability is built into every Entity Flow and Entity Value output.
What I'm Building Now
Entity Flow (US): Operational decision intelligence for US hospitals. Currently piloting with hospital systems on staffing and capacity decisions—where every choice carries real financial and clinical stakes. Entity Flow produces auditable decision packets that operations teams can justify, stress-test, and defend.
Entity Value (Korea): Decision evaluation systems for Korean government and institutional clients, with frameworks adopted across public-sector organizations.
Research: Writing about decision-making under uncertainty, practical AI governance, and why most operational problems in healthcare are governance problems before they're analytics problems.
Follow My Thinking
I write about decision-making under uncertainty, AI governance, and healthcare operations.
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