The people behind Lumecon’s models, data and platform.

Eight years producing tribal economic-impact studies and related public-policy research.

Senior Research Assistant at the Center for Indian Country Development at the Federal Reserve Bank of Minneapolis. There he led the construction of the Native Entity Enterprise Dataset, the first comprehensive dataset of Native entity enterprises, and launched and led research on Native federal contracting.

Research Fellow at the Project on Indigenous Governance and Development at the Harvard Kennedy School, and a co-author of the third edition of Social and Economic Changes in American Indian Reservations.

Previously a research analyst at the Taylor Policy Group and a Wilma Mankiller Fellow at the National Congress of American Indians.

Enrolled member of the Coastal Band of the Chumash Nation, a non-federally recognized tribe in California.

Economist at the Center for Indian Country Development at the Federal Reserve Bank of Minneapolis before joining Lumecon.

Previously a tenure-track economics professor at the University of Alberta.

Builds Lumecon's regional input-output models and multiplier system, connecting source data to reviewable economic impact estimates.

Previously worked on economic modeling and public-sector data science for the District of Columbia government, the Board of Governors of the Federal Reserve System and the Federal Reserve Bank of Philadelphia.

Builds the intake and assumption-review systems that help Cedar turn organizational records into structured, reviewable analysis.

Also contributes to Lira, an AI wearable company.

Builds the platform organizations use to scope, run and revisit analyses.

Also contributes to Lira, an AI wearable company.

Founder and CEO of Lira, an AI wearable company.

Previously a senior software engineer at Modsy and Chime.

NSF Graduate Research Fellow.

His research has appeared in American Economic Review: Insights.

Builds data-governance and privacy practices for sensitive administrative data.

Supports cross-agency data sharing and research operations.