Grants Advancing Community-Led AI Research to Improve Health

Grants Advancing Community-Led AI Research to Improve Health is sponsored by AIM-AHEAD collaborative initiative (Various). This initiative provides funding opportunities for expanding AI/ML research to enhance health outcomes for diverse populations.

We're a community of 10,000+ Artificial Intelligence and Healthcare Experts Lead, recruit, and coordinate the AIM-AHEAD Consortium Data Science Training Core Assess, develop, and implement data science training curriculum Assess data and computing infrastructure for AI/ML and health research Address priorities and needs for AI/ML research with electronic health records Save the Date: 2026 AIM-AHEAD Annual Meeting July 6 - 9, 2026 | San Diego, CA Connect with innovators driving the future of AI/ML in health.

The 2026 AIM-AHEAD Annual Meeting will convene researchers, institutions, community partners, and program leaders from across the country to share insights, showcase innovation, and strengthen the national AIM-AHEAD ecosystem. Together, we’re building the workforce, infrastructure, and partnerships needed to transform healthcare through AI/ML. The 2026 AIM-AHEAD Annual Meeting website is now live!

Explore the conference agenda, featured events, and important details by visiting the link below. 2026 AIM-AHEAD Annual Meeting Website what's happening at aim-ahead AIM-AHEAD Consortium News & Updates Explore the latest news, stories, and initiatives shaping the future of AI/ML healthcare innovation across our national network.

AI Optimization Subcore Office Hours and Discussion Forum Dr. Huang, an Assistant Professor of University of Pennsylvania Perelman School of Medicine Pathology and Laboratory Medicine, will discuss the critical role of building an integrated ecosystem for medical imaging and demonstrate how AI can assist pathologists to enhance diagnostic accuracy and efficiency through multiple AI algorithm development efforts.

AIM-AHEAD Research Spotlight Series: Showcasing Innovative Research Across the Consortium Find out more about how AIM-AHEAD CLINAQ Program participants Kalyani Narra (MD) and Dhruvangi Sharma (PhD) are advancing healthcare through AI/ML-driven research.

Johns Hopkins University Vibe Coding Sessions Register now to attend the coding session two, where Dr. Gordon Gao from Johns Hopkins University will explore practical, AI-assisted approaches to research, innovation, and problem-solving.

National Distribution of AI/ML Researchers on AIM-AHEAD Connect Join AIM-AHEAD Consortium We are a community of 10,230 researchers focused on leveraging AI/ML in biomedical research to improve healthcare, including 6,670 trainees, 2,330 experts, and 190 active discussion groups. AIM-AHEAD Connect is developed and maintained by the Communications Hub . Connect with a vast network of mentors and mentees nationwide for advice and guidance.

Build your Mentoring network to further your career, upload your CV, search for members and their CVs and research interests. Learn through free AI/ML courses designed for researchers, clinicians, and innovators. Explore the full course catalog and advance your skills today.

Collaborate with other members in the AIM-AHEAD Connect network by joining groups, add status updates, share files, messaging, and search features. “Hallmarks of Success” are goals for the AIM-AHEAD Consortium to strive towards. These hallmarks have been aligned to AIM-AHEAD’s four North Stars, and is included in the AIM-AHEAD Coordinating Center (A-CC) evaluation plan.

Cores, hubs, and consortium partners will report on how their activities contribute to which hallmark(s) to track progress.

Develop a representative AI/ML workforce with broad participation Increase knowledge, awareness and national-scale community engagement and empowerment in AI/ML Use AI/ML to improve behavioral health, cardiometabolic health and cancer outcomes for all Build community capacity and infrastructure in AI/ML to address community-centric health challenges AIM-AHEAD Workforce Development Programs Discover the national impact of our AIM-AHEAD Workforce Development Programs by exploring the map on the right.

This map highlights the sixteen innovative initiatives and training collaborations that have been launched since 2022, including all program cohorts from Year 1 to Year 4. Visit our Programs page to learn more about how these AIM-AHEAD initiatives are shaping the future workforce in artificial intelligence, machine learning and healthcare by engaging hundreds of award recipients across the country.

AIM-AHEAD Research Programs Explore the national impact of our AIM-AHEAD Research Programs by viewing the map to the left. This map highlights the seven distinguished research initiatives launched since 2022, covering all program cohorts from Year 1 to Year 4.

To learn more, visit our Programs page and see how these AIM-AHEAD programs are empowering researchers to leverage and enhance their capacity for artificial intelligence and machine learning, enabling them to conduct meaningful research nationwide.

aim-ahead program spotlight Program for Artificial Intelligence Readiness Through the implementation of a two-phase funding model, PAIR has connected awardee institutions from across the United States with AIM-AHEAD resources, AI/ML and health experts, and grant-writing coaches to help establish AI/ML Health Research Labs which host cross-disciplinary teams for research projects and grant writing.

AIM-AHEAD Connect Course Spotlight Course: MATCH Workshop Series Two new modules, 'Predictive Modeling Using Healthcare Data', and 'Microscopy Image Analysis', are now available in the MATCH Workshop Series course on AIM-AHEAD Connect. The course provides a practical introduction to the use of artificial intelligence in biomedical research.

Participants will explore applications of AI across diverse areas including electronic health records (EHRs), computer vision, generative AI, adaptive learning, and federated learning. Through a mix of conceptual overviews and hands-on examples, learners will gain the tools and knowledge needed to evaluate, apply, and adapt AI methods in their research.