Regenerative Engineering and Medicine Center (REM) Collaborative Grant Program

Emory University, Georgia Institute of Technology, and University of Georgia under the Regenerative Engineering and Medicine Center (REM) announce the 2025-26 collaborative grant program. This funding mechanism is intended to stimulate new, collaborative research in regenerative medicine among Georgia Tech, Emory University, and UGA investigators. The collaborative grant team must have a minimum of two investigators and must have an equal partnership of faculty from two of the participating institutions with budgets split between the universities as equally as possible.
This funding mechanism may support collaborative projects at earlier stages of development in the “high risk, high yield” category or projects with exceptionally innovative or novel technology and/or a high potential for clinical or industry translation. Budgets for these proposals may not exceed $100,000.
2025-26 Seed Grant Mechanism: Focus on AI and Regenerative Medicine
In addition to our core focus areas, we are particularly interested in proposals that explore the intersection of regenerative medicine and artificial intelligence (AI). With the rapid evolution of computational technologies, AI is poised to transform the landscape of regenerative medicine — from predictive modeling and image-guided diagnostics to personalized therapeutic design and outcome forecasting.
Proposals that aim to integrate AI tools (e.g., machine learning, data mining, neural networks, natural language processing) into the discovery, development, or delivery of regenerative therapies are strongly encouraged. This includes efforts to leverage large-scale datasets, enhance tissue engineering strategies, optimize stem cell applications, or improve understanding of complex biological systems through computational modeling. Collaborative projects that combine expertise in regenerative medicine with AI, bioinformatics, systems biology, other computational disciplines will be viewed favorably. Projects that demonstrate potential for translational impact or significantly advance our capacity to model, predict, or manipulate regenerative processes using AI will be given priority.