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Clinical & Translational Science Institute / Funding / Digital Health Seedling Award

Digital Health Seedling Award

Digital Health Seedling awards are designed to promote innovative, high-risk research that advances the development, approval, adoption and use of innovative digital health tools, methods and approaches. Preference will be given to proposals that are innovative, interdisciplinary and have a high potential for significant impact.

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The principal investigators (PI) on all proposals must be a full-time faculty member at the University of Rochester. Each faculty member can participate in only one application.

Applications may exploit a range of digital health approaches, tools and data, including topics in the areas of:

  • Electronic medical records
  • Sensors and mobile technologies
  • Real-World Data/Evidence
  • Social media
  • Other approaches and tools focused on advancing clinical research and addressing regulatory science needs

Funding Amount

The award provides a maximum of $25,000 for a period of one year.

Important Dates

The following dates apply to the current solicitation:

  • Proposals due – March 25, 2024 at 5:00 p.m.
  • Notification of award​ – May 8, 2024
  • Anticipated start date​ - July 1, 2024
  • Award period ends​ - June 30, 2025 

Note, no funds are allowed to be carried forward.


Application Inquiries

Karen Grabowski -

Scientific or Programmatic Questions

Jean-Philippe Couderc, PhD, MBA -
Joan Adamo, PhD -


2024 RFA for the Digital Health Seedling Awards
CTSI Cost Sharing Information
CTSI Signoff Form 11/2021

Ready to Apply?

Start Application

Need Teleresearch Training?
We offer a teleresearch training course in Blackboard that covers the basics of remote research and highlights available resources and support for conducting teleresearch at the University, including information and resources on digital health technologies. To access the course, log into Blackboard, search for "CTSI Teleresearch training," and self-enroll.

Scholars and Projects


Comprehensive Real-Time Assisted Deep Learning in Extremely Low Gestational Age Newborns (CRADLE)
Andrew Dylag, MD
, Associate Professor, Department of Pediatrics, University of Rochester Medical Center


Prototype of novel care-path-based indicator of health equity for older adults with heart and lung disease
Julie Ryan Wolf – Associate Professor in the Department of Dermatology at the University of Rochester Medical Center
Elaine Hill – Associate Professor in the Department of Public Health Sciences at the University of Rochester Medical Center 


Measurement and relationship of physiological arousal and stress in children with autism spectrum disorder and caregivers
Suzannah Iadarola, Ph.D.,
Assistant Professor of Pediatrics at the University of Rochester Medical Center
Kenneth Shamlian, Psy.D., Assistant Professor of Pediatrics at the University of Rochester Medical Center
Samantha Daley, Ed.D., Assistant Professor of Counseling & Human Development at the University of Rochester Warner School of Education
Zhi Zheng, Ph.D., Assistant Professor of Biomedical Engineering at the Rochester Institute of Technology


Remote Longitudinal outcome assessments in amyotrophic lateral sclerosis: Laying the foundation to overcome diagnostic delays through remote digital technologies and machine learning
Peter Creigh, M.D.,
Assistant Professor of Neurology at the University of Rochester Medical Center


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