Research
Founder & CEO, Doogooda · Harvard PhD · Former faculty (Operations/Tech)
I study how institutions make decisions under uncertainty—and I build the systems that make those decisions auditable.
My work bridges decision science and deployment, focusing on auditable decision systems for regulated operations in healthcare, public policy, and AI governance. The research behind Doogooda's products—Entity Flow and Entity Value—is grounded in this work.
Method: Causal inference → scenario simulation → constrained optimization → auditable decision artifacts.
Affiliation & Background
gBETA accelerator (gener8tor)
Selected, Spring 2026. Madison, WI.
Seoul National University
Visiting Researcher, Cognitive AI Lab (2024–Present)
Rotman School of Management, University of Toronto
Teaching Case Subject & Guest Lecturer (2026)
UCL School of Management
Former Assistant Professor, Operations & Technology
Selected Publications
Healthcare Operations · Management Science · 2023
The Impact of Vertical Integration on Healthcare Delivery
How physician–hospital integration affects care quality and costs. Using US Medicare claims data to study market structure effects on hospital behavior. With Saghafian, Newhouse, Landrum, and Hsu.
Healthcare Operations · Production and Operations Management · 2024
Facility Closure Decisions Under Regulatory Constraints: A Causal Inference Approach
How to structure facility closure decisions when regulatory constraints bind. Framework adopted by US academic medical centers.
Healthcare Policy · Harvard PhD Dissertation · 2020
Causal Inference for Healthcare Operations Under Policy Constraints
Methodological framework for decision-making in regulated healthcare contexts.
Forthcoming Presentations
Healthcare Policy · AcademyHealth Annual Research Meeting · 2026
Using Claims Data to Simulate COVID Payment Policies: Urban-Rural Access and Equity Trade-Offs In Gyeonggi Province, South Korea
Poster presentation. Seattle, WA. June 1, 2026.
Healthcare Policy · AcademyHealth Annual Research Meeting · 2026
Algorithmic Health Advertising In Non-Clinical Settings: A Cluster-Randomized A/B Test Shows Adverse Access and Utilization Shifts In Lower Provider-Density Areas In South Korea
Poster presentation. Seattle, WA. May 31, 2026.
Healthcare Operations · SMDM 48th Annual Meeting · 2026
Algorithmic Health Advertising In Non-Clinical Settings: A Cluster-Randomized A/B Test Shows Adverse Access and Utilization Shifts In Lower Provider-Density Areas In South Korea
Poster presentation. Oslo, Norway. June 30, 2026.
Teaching & Invited Presentations
Rotman School of Management, University of Toronto
Guest Lecturer, MBA & Global Executive Healthcare MBA (May 2026)
Teaching case: "Doogooda's Entity Flow: Moving from South Korea to the USA"
Prof. Dilip Soman
The Chinese University of Hong Kong (CUHK)
Guest Speaker, Co-op Field Trip Program (2026)
Seoul, South Korea
Baekseok University K-HiTech Platform
Invited Speaker, AI & Drone Conference (November 2025)
"Autonomous Flight: Accountability, Safety Standards, and Data Governance"
Seoul, South Korea
Durham University
Guest Lecture (2026, scheduled)
MAAI SIG Webinar
Decision Systems Deployment in Healthcare (scheduled)
Press
Applied Insights
Frameworks and analysis connecting research to practice.
Decision-making under uncertainty
Trade-offs, governance, and how to structure choices when outcomes are unknowable.
From dashboards to decisions
How to operationalize "what to do" instead of "what happened."
US–Korea institutional comparison
What transfers, what doesn't, and why context matters for policy.
Elections as decision systems
Uncertainty, causal claims, and governance frameworks for electoral and policy interpretation.
Academic Background
Harvard PhD (Decision Science, Health Policy) · Yale MA (Statistics) · Caltech BS (Applied Math)
Affiliations: Visiting Researcher, Seoul National University Cognitive AI Lab · Former Assistant Professor, UCL School of Management