Laurah Turner

WORK HISTORY

EDUCATION

ABOUT LAURAH TURNER

I am the Associate Dean for Artificial Intelligence and Educational Informatics and an Associate Professor of Bioinformatics, Health Statistics and Data Science, and Medical Education at the University of Cincinnati College of Medicine. I design and study AI‑driven systems that support precision medical education—linking learning analytics, machine learning, natural language processing, and data science to the day‑to‑day realities of teaching, learning, and assessment. Turner CV 2025My work focuses on three main areas:• AI‑enabled assessment and feedback – multi‑agent simulations, ambient AI feedback during clinical encounters, and tools that turn narrative and conversational data into actionable insight for learners and faculty.• Curriculum intelligence and learning analytics – AI‑assisted curriculum mapping, dashboards, and data pipelines that help educators monitor progress, align assessments, and make timely interventions.• Responsible AI implementation in medical training – practical frameworks, toolkits, and governance strategies for using LLMs and other AI tools in ways that are transparent, explainable, and aligned with professional standards. I lead 2‑Sigma Labs, an innovation hub within the College of Medicine, where we build AI‑based platforms for question generation, clinical reasoning support, and personalized coaching. Our teams have multiple patents pending and are actively translating research prototypes into scalable tools for medical schools and training programs. As PI or co‑PI, I have secured multi‑site funding from organizations such as the American Medical Association and the American Board of Internal Medicine to study AI‑supported assessment, clinical reasoning, and precision feedback in medical education. I also serve on national advisory groups (AAMC, ABMS, AMA and related consortia) focused on AI in admissions, assessment, and educational technology. I collaborate closely with residents, fellows, medical students, and PhD trainees, integrating them into the full lifecycle of AI tools—from concept and model design to validation and dissemination. Together, we have produced peer‑reviewed publications, national presentations, and award‑winning innovations in AI‑enabled medical education.