Grover Lab Grover Lab / Clinician-Developer Training
Research Area

Clinician-Developer Training

We study how clinicians learn to supervise, specify, evaluate, and help build AI-enabled tools. The goal is not to turn every clinician into an engineer. It is to train people who can work across clinical workflow, educational design, and technical development.

Clinician-developer training at Grover Lab

Current work

We create programs for clinicians to learn how to build and supervise AI-enabled tools, including a Clinical AI Developer Fellowship targeting a July 2027 start and an elective for medical students and residents. In parallel, we are studying how clinicians specify real problems, work with builders, and evaluate whether a tool actually fits clinical and educational workflow.

Selected links

Integrating artificial intelligence into endoscopy training: opportunities, challenges, and strategies. Grover SC, Walsh CM. Lancet Gastroenterology & Hepatology. 2024. Gastrointestinal Endoscopy Clinics of North America article in press. Gimpaya N, Landy J, Tran WT, Grover SC. Abstract link for a new 2026 publication in this research area. The AI stack for the medical student or resident An opinionated guide to the tools medical learners should be using right now. I became a good doctor by doing it badly first Why the apprenticeship model that makes doctors depends on fumbling — and what AI means for that. The AI agent-augmented physician A short statement of the shift from execution alone to supervising delegated work. Agentic AI in medical education Why agents matter in training environments because they act, persist, and produce artifacts. Who trains the trainers? Why faculty capability is part of the infrastructure problem.

FAQ

Who leads this work? Samir C. Grover leads Grover Lab's work in clinician-developer training at Scarborough Health Network and the University of Toronto.
What programs are being built now? We are building a Clinical AI Developer Fellowship targeting a July 2027 start and arranging an elective for medical students and residents.

Stay in the loop

Occasional essays on AI, simulation, and the future of medical education.