Program Structure and Resources

Through a series of lectures, guided projects, and IRB supported basic research, Program members develop algorithms to explore diagnostic spaces in pathology from cancer detection, to gigapixel image manipulation, to text prediction. Students are placed into teams to design and pitch projects and adhere to a team culture which promotes broad collaboration. Dr. Levy meets weekly with lab project teams to discuss updates and provide guidance on the technical aspects of their projects (including presentation/manuscript preparation), while providing tutorials (e.g., overview of operating in an HPC environment), a lab GitHub based wiki page, and over the summer a weekly seminar series Seminar series to help them better understand emerging themes in the field. Dr. Levy also holds weekly office hours for general inquiries.

Immersing high school students in responsible, real-world AI research to transform the future of medicine.

Why this program exists:

Artificial intelligence technologies are increasingly integrated into modern healthcare — from protein structure prediction and computational genomics to risk stratification models and digital pathology workflows. While these systems hold transformative potential, they also raise important concerns regarding bias, equity, reliability, and trust.
Preparing the next generation of researchers and clinicians requires more than technical proficiency. Students must learn to critically appraise algorithmic limitations, anticipate failure points, and ensure that AI tools align with the realities of clinical practice and stakeholder needs.
EDIT AI was created to meet this need.