AI for Health Seed Grant

AI for Health Seed Grant is sponsored by Washington University in St. Louis (Office of the Vice Chancellor for Research and AI for Health Institute). Supports innovative and interdisciplinary research that leverages Artificial Intelligence (AI) to address critical challenges in health.

Designed to catalyze collaborations across disciplines, encouraging the integration of AI with public health and health care.

AI for Health Seed Funding Program | AI for Health Institute (AIHealth) | Washington University in St. Louis The AI for Health Seed Grant supports innovative and interdisciplinary research that leverages artificial intelligence (AI) to address critical challenges in health . This program is designed to catalyze collaborations across disciplines, encouraging the integration of AI with public health and health care.

Projects must bring together researchers from AI and health domains to forge new paths to solve significant health problems with advanced AI technologies. This program runs annually. This seed grant is a collaboration between the AI for Health Institute and the University’s seed grant program, run by the Research Development Office .

Proposals due Mar. 4, 2026 Learn more about eligibility and required application materials Co-Principal Investigators (co-PIs) must be full-time faculty at WashU at the time of application and remain so for the award’s duration. There must be a tangible collaboration from at least two schools within WashU (a minimum of two co-PIs must have primary appointments from different schools).

Please note that there is no distinction between co-PI and PI as these are fundamentally collaborative grants. Applicants may be Co-PI on one application per AI for Health cycle. All co-PIs must be current on their reporting from any previously received university-wide seed grants (including AI for Health, Spark Funding, Ignite, and Transcend Initiative grants, etc.) to be eligible for subsequent awards.

Proposals submitted to this competition should not be under review in any other university-wide seed grant competition. Review process & timeline The AI for Health seed grant will use a panel of peer reviewers across interdisciplinary areas of AI and health. The names of the reviewers are confidential.

Applications will be reviewed as swiftly as possible with notification of award in early summer 2026 and an award start of July 1, 2026. All applications must be submitted via the InfoReady platform. General Tips & Guidelines Applicants should address each element discussed in the Evaluation criteria in the body of their proposal.

All responses should be written to be understandable to non-specialists. It is recommended that applicants do not repurpose previously submitted grants but concentrate on responding to the criteria articulated below, especially as it is expected that proposals for this program have not yet been funded.

Part I: Team Information & Project Summary Enter the names, appointments, schools, departments, and emails of the project’s co-PIs Enter the name of the staff who would be the post-award administrator, if awarded Project Abstract—150 words free of jargon, for a general academic audience Part II: Project Description Project descriptions should be written for an interdisciplinary audience across AI and health.

In no more than 3 pages (single spaced, 1-inch margins, font no smaller than 11 pt.) applications must explain the following: Research What is the specific AI-driven health research being proposed? Clearly articulate the innovation and novelty of your approach, emphasizing how AI is being applied to address a significant health challenge.

Describe the potential impact of this research on health outcomes and its contribution to the field of AI in health. Team Composition and Roles Identify the researchers involved in this project, detailing their roles and responsibilities. Explain how the interdisciplinary expertise of the team is crucial to the success of the project, particularly in integrating AI with health-related disciplines.

Highlight how each member’s unique background and skills contribute to a comprehensive approach to the research question. New Line of Inquiry Describe how this project represents a novel research direction for the team, particularly in the context of AI for Health. Clearly explain how the project is exploratory and not an extension of already funded work.

Explain why this seed funding is essential for initiating this new line of research. Planned Activities Outline the specific activities that the team will undertake during the award period that the funds will enable. Describe how these activities will advance the project, including any preliminary data collection, algorithm development, or pilot studies that will set the foundation for future research activity.

Part III: Budget and Budget Justification If there are any questions about allowable costs, please reach out to researchseedfunding@wustl. edu to confirm.

Up to $50,000 over one year Non-faculty personnel (postdoctoral fellows, students, and staff) Research materials (such as data sets, lab supplies, etc.) Equipment or capital expenses Generally unallowable costs are: Research costs outside of Washington University Part IV: Additional Information & Uploads Upload Biosketches in the NIH format for each co-PI, combined into a single . pdf file.

Include only the most relevant and recent publications and research, no more than 4 pages per co-PI. Upload Other Support document (NIH format) for each co-PI combined into a single . pdf file.

This should include all active research funding pending, external and internal. Optional Supplementary Upload: Please limit this to one page of information. This may include a concept graphic, a program of activities, etc. Innovative Excellence and Impact in AI and Health : The proposal should clearly articulate how the research will advance public health or healthcare through the innovative use of AI.

Submissions will be evaluated on both the potential health impact and the strength of the AI methods. The research proposed should be impactful and cutting edge, designed to push the boundaries of what is currently possible in AI for Health. Collaborative Excellence: The co-PIs listed on the proposal are from varying academic and scientific disciplines.

The work proposed cannot be done without one of the research partners listed. There are clear pathways for the work to move the needle in the disciplines of each researcher, and in the broader area of AI for Health. Clarity and Feasibility of Proposed Research Activities: The research activities described are feasible in the timeline given and with the resources requested.

The budget provided clearly justifies the planned activities. Personnel support is reasonably justified and their contribution to the project described. Clarity and Feasibility of Potential Funding Pathways: The pathway to subsequent funding is clearly detailed in the proposal and the research activities described will allow the team to become more competitive for the prospective external funding sources.

A report detailing project activities, outcomes, and fiscal expenditures will be due 90 days after the award period’s end. There will be another follow-up one year after award period end. All reports will be in the InfoReady system.

Lora Iannotti , the Lauren and Lee Fixel Distinguished Professor in the WashU School of Public Health, in collaboration with Bo Li , the Stanley A. Sawyer Professor of Statistics and Data Science, who received $49,725 for a project titled “Integrated Mobile AI Technology for Global Infant Nutrition Evaluation (IMAGINE).

” Denise Wilfley , the Scott Rudolph University Professor of Psychiatry, Medicine, Pediatrics and Psychological & Brain Sciences and director of the Center for Healthy Weight and Wellness at WashU Medicine, in collaboration with Ellen Fitzsimmons-Craft , associate professor of psychiatry and psychological and brain sciences in Arts & Sciences; Rick Stein , professor of medicine at WashU Medicine; and Jiaxin Huang , assistant professor of computer science & engineering in the McKelvey School of Engineering, who received $50,000 for a project titled “AI-Enhanced Interventionist Certification and Ongoing Fidelity Monitoring for Digital Family-Based Treatment of Childhood Obesity.

” Matthew Thomas, MD , instructor of medicine at WashU Medicine, in collaboration with James Duncan, MD , professor of radiology at the Mallinckrodt Institute of Radiology (MIR) at WashU Medicine and associate director of interventional radiology at St.

Louis Children’s Hospital, and Abhinav Jha, associate professor of biomedical engineering in McKelvey Engineering, who received $50,000 for a project titled “Leveraging Videos and Connected Multimodal Metadata to Achieve Procedural Intelligence in Interventional Radiology.

” Mengxin Yu , assistant professor of statistics and data science in Arts & Sciences, in collaboration with Jin Zhang , associate professor of radiation oncology; Thomas Mazur , associate professor of radiation oncology and chief of stereotactic body radiation therapy; and Michael Waters , MD, PhD, assistant professor of radiation oncology, all of WashU Medicine, who received $50,000 for a project titled “MAESTRO — Multi-Agent Evolutionary System for Treatment in Radiation Oncology.

” Arindam Mukherji, assistant professor of physics in Arts & Sciences, in collaboration with Xiaoxia Cui , associate professor of genetics and director of the Genome Engineering & Stem Cell Center at WashU Medicine, who received $50,000 for a project titled “Developing AI Virtual Cell Models to Predict Stem Cell Differentiation from Organelle Dynamics.

” Michael Harris , associate professor of physical therapy, of orthopedic surgery at WashU Medicine and of mechanical engineering & materials science in McKelvey Engineering, in collaboration with Tao Ju, professor of computer science & engineering in McKelvey Engineering, who received $50,000 for a project titled “AI-Assisted Image Segmentation and Surface Reconstruction of the Hip Across the Lifespan.

” Full announcement: AI for Health seed grant program awards nearly $300,000 to advance AI-driven health research Abhinav Jha, associate professor of biomedical engineering in McKelvey Engineering and of radiology at WashU Medicine Mallinckrodt institute of Radiology, in collaboration with Barry Siegel, MD, professor of radiology and of medicine, and Farhan Katchi, MD, assistant professor of medicine, both at WashU Medicine: $49,977 for a project titled, “Clinical Implementation of CTLESS for Accessible, Affordable, Accurate, and Safer Diagnosis of Coronary Artery Disease.

” Lan Yang, the Edwin H. & Florence G. Skinner Professor of Electrical & Systems Engineering, in collaboration with Joseph Gaut, MD, Ladenson Professor of Pathology & Immunology, and Jose Saenz, MD, assistant professor of medicine, both at WashU Medicine: $50,000 for a project titled, “AI-Enhanced Hyperspectral Imaging for Virtual Tissue Staining and Automated Pathology Analysis.

” Matthew Brier, MD, PhD, assistant professor of neurology at WashU Medicine, in collaboration with Ulugbek Kamilov, associate professor of electrical & systems engineering and of computer science & engineering: $50,000 for a project titled, “Lesion Expansion Screening via Artificial Intelligence (LESION-AI).

” Guy Genin, the Harold and Kathleen Faught Professor of Mechanical Engineering, in collaboration with Mohamed Zayed, MD, PhD, professor of surgery and of radiology, and Josh Osbun, MD, professor of neurosurgery, of radiology and of neurology, both at WashU Medicine: $50,000 for a project titled, “AI-NAVIGATE: Patient-Specific Tool Selection for Endovascular Procedures through Physics-Informed AI Research.

” Joshua Oltmanns, assistant professor of psychological & brain sciences in Arts & Sciences, in collaboration with Nathan Jacobs, professor of computer science & engineering: $50,000 for a project titled, “Advancing Psychological Assessment with Computer Vision AI.

” Fanwei Kong, assistant professor of mechanical engineering & materials science, in collaboration with Pirooz Eghtesady, MD, PhD, chief of pediatric cardiothoracic surgery at WashU Medicine: $50,000 for a project titled, “AI and Computational Simulator for Pre-Operative Planning of Pediatric Mitral Valve Surgeries.

” Full announcement: Inaugural AI for Health seed funding program awards nearly $300,000 Please reach out to researchseedfunding@wustl. edu with any questions about this or other university-wide seed grants.