EMBÍ·NET
Work & ImpactFocus areas

What he works on

Four decades’ worth of one idea: that medicine advances fastest when knowledge is computable, connected, and worthy of trust.

01
Clinical research informatics

A field he helped found

Embí is credited among the founders of clinical research informatics — the discipline that uses electronic health records and health data to make biomedical research faster, broader, and more rigorous. His early studies of EHR-based clinical trial recruitment and of computerized clinical documentation became widely cited reference points for the field.

02
Trustworthy AI

Algorithmovigilance

Embí conceived and named algorithmovigilance: the systematic, ongoing surveillance of clinical AI after deployment for safety, bias, and performance drift — modeled on the way medicine monitors drugs once they reach patients. It reframes AI safety as a continuous, operational responsibility rather than a one-time approval.

  • Originated the concept and the term now used across the field
  • Leadership in national efforts on the responsible use of health AI
03
Learning health systems

Closing the loop between care and discovery

Across roles at IU Health, Regenstrief, and Vanderbilt, Embí has built systems where everyday care and research continuously inform each other — so health systems learn and improve as a matter of routine rather than exception.

04
Knowledge infrastructure

Computable, AI-ready knowledge

Turning the medical record and the medical literature into structured, connected, machine-usable knowledge — and governing it for integrity, so that what clinical AI learns from can itself be trusted.

Current efforts

In progress · since 2025
Vanderbilt ADVANCE AI Center

Founding Director

Leading Vanderbilt’s center for the development, evaluation, and responsible deployment of artificial intelligence across the medical center’s research and care missions.

AI governance · Vanderbilt

Oversight & standards

Directing how clinical AI is reviewed, monitored, and held accountable across the institution — putting algorithmovigilance into operational practice.

VAMOS Collaborative

Open-source governance & monitoring

An open-source community for the governance and monitoring of clinical AI, built on VAMOS — a technology Embí developed at Vanderbilt and licensed for wider use.

TRAIN

Trustworthy & Responsible AI Network

A learning network generating the real-world evidence needed for responsible, effective AI in health care — shared across institutions rather than siloed.