About
Decision Architect · Harvard PhD · Former faculty (Operations/Tech) · Founder & CEO of Doogooda (Decision Systems)
I build accountable decision systems for regulated, high-stakes operations—where constraints, governance, and trade-offs matter as much as accuracy.
I'm the Founder & CEO of Doogooda — building auditable decision workflows for regulated operations.
Method: Causal inference → scenario simulation → optimization. Bridging decision science and deployment across healthcare operations and public policy.
What I Ship: Auditable decision packets—evidence, constraints, trade-offs, and decision logs—so institutions can approve actions, not "AI recommendations."
Media Kit
Speaking
Editorial
On Stage
Focus Areas
Decision Systems
Frameworks for structuring choices under uncertainty—from elections and policy interpretation to institutional risk. Trade-offs, constraints, and governance.
Healthcare Operations
Clinical operations as policy-native decision intelligence. Causal inference in practice.
AI Governance
Auditable AI for real institutions. Moving beyond explainability to accountability.
Credentials & Affiliations
How I Work
Evidence-first
I label what's known vs. what's to-verify. No hidden assumptions.
Trade-offs
I write the trade-off table, not just the recommendation.
Decision memos
Every call has an auditable trail.
What I'm Building Now
Doogooda: Building decision systems that make their logic auditable—what assumptions changed, which constraints are binding, what trade-offs are being accepted. A decision trail that matters in regulated contexts.
Research: Writing about decision-making under uncertainty, practical AI governance, and policy-native decision intelligence.
Selected Press
"AI autonomy requires accountability & governance"
Autonomous systems must embed governance structures from design.
Connect