Expanding the Use of Collaborative Data Science at UM Grant Program

Young Professor working on laptop

This program is designed to increase the use of data science to foster breakthroughs in disciplinary pursuits making the research team more competitive for external funding. Applications are required to include at least one data scientist from the Frost Institute for Data Science and Computing (IDSC) and one researcher from a specific discipline. Typically, the disciplinary researcher initiates and leads the project. The IDSC data scientist acts as a high-level consultant to ensure the proposal has enough data science.

Funding

The awards include $20K discretionary funds[1] and 1M Service Units (SUs) to be used for high performance computing (HPC). It is anticipated that five awards will be made.

Theme

For the 2025-2026 academic year, IDSC seeks proposals that address the following:

  • Using data science to improve access to healthcare, and accelerate services and improve healthcare efficiency

Other topics and issues are also welcome. Pre-submission inquiries are encouraged.

In terms of this grant opportunity, data science is defined as utilizing state-of-the-art approaches such as Machine Learning (ML) or Artificial Intelligence (AI) to enable scientific discovery that is data driven. Simply, proposing to analyze large data sets with traditional techniques (e.g., linear regression) is not responsive to this opportunity. Proposals that use AI/ML to develop new understanding are strongly encouraged.

How to Apply

The application process includes two steps:

Step 1:  The disciplinary researcher provides a one-page letter of intent to IDSC outlining the discipline specific research and where data science fits in. Based on the letter of intent, the IDSC review team will identify an IDSC data scientist for collaboration, if the research team has not already identified an IDSC partner. Applications now closed.

Step 2: Upon invitation to advance to Step 2, the research team with assistance from the IDSC data scientist will prepare a two-page proposal that outlines the research and the data science plan. The proposal should also include a short discussion of potential external funding mechanisms that the proposed work can be used to enhance the competitive position of the research team. The application should include an abbreviated one-page biosketch and a budget with justification using the templates included in this announcement. All documents should be combined into a single .pdf.  Step 2 now closed.

Eligibility

This funding opportunity is open to UM Faculty with an active IDSC membership.  For more information on IDSC memberships and to apply, visit https://idsc.miami.edu/membership/.

Reporting

The research team is required to submit an interim report midway through the performance period.  The one-page report should include a brief description of the project’s progress and an overview of the financial situation. Upon project completion, the research team will submit a one-page final report detailing any accomplishments attributed to the work of this project (publications, proposal submission(s) for extramural funding, data sets generated, etc.) and give an oral presentation describing the research and results as part of IDSC’s seminar series. Scheduling of the oral presentation will be coordinated by IDSC’s Engagement Office.

Review Process

Applications will be reviewed by the evaluation committee to determine feasibility, relevance to IDSC programs, and in terms of how the proposed research will put the team in a more competitive position for external funding.

Important Information and Deadlines

  • Click here for the recording of the Zoom INFO session led by Ben Kirtman back on September 10 (30 minutes).
  • Step 1 – Letters of Intent:  Due by 5:00 PM, Tuesday, September 30, 2025. 
  • Invitation to submit full proposal in Step. 2 with identification of an IDSC data scientist partner (if applicable):  October 17, 2025.
  • Step 2 – Two-page proposal: Due by 5:00 PM on Friday,  November 21, 2025
  • Notice of Award:  On or before December 19, 2025
  • Project performance period:  January 1, 2026 – December 31, 2026.
  • Interim Report Due on June 30, 2026
  • Service Units (SU) expire January 31, 2027
  • Final Report Due on February 28, 2027
  • Oral Presentation of Results Due in Fall 2027/Spring 2028

Review Committee

Mairead Moloney
Mairead Moloney
Anna Carolina Muller Queiroz
Kaan Inal
Kaan Inal
Daniel Messinger
Ben Kirtman
Ben Kirtman

 

 

 

 

 

 

 

 


[1] Discretionary funds can be used for salary, travel, and other research-related expenditures as outlined in the proposal budget.  Equipment purchases are not allowed.

 

Fall 2025 Awardees  | All Awardees

Kilan C. Ashad-Bishop, PhD, Fall 2025 IDSC Grant Awardee, University of Miami Frost Institute for Data Science and Computing "Expanding the Use of Collaborative Data Science at UM" Grants Program

Kilan C. Ashad-Bishop, PhD

Associate Professor
UNIVERSITY OF MIAMI
Rosenstiel School of Marine, Atmospheric, and Earth Science
Department of Environmental Science and Policy

“Leveraging Earth Systems Data to Advance Health System Resilience”

Christina Cordero, PhD, Fall 2025 IDSC Grant Awardee, University of Miami Frost Institute for Data Science and Computing "Expanding the Use of Collaborative Data Science at UM" Grants Program

Christina Cordero, PhD

Research Associate Professor
Co P.I. Hispanic Community Health Study/Study of Latinos
UNIVERSITY OF MIAMI
College of Arts and Sciences
Department of Psychology

“Identifying Modifiable Risk Profiles to Improve Healthcare Access and Inform Cardiometabolic Interventions in Hispanic/Latino Adults Using Machine Learning”

Brooke Crawford, MD MBA, Fall 2025 IDSC Grant Awardee, University of Miami Frost Institute for Data Science and Computing "Expanding the Use of Collaborative Data Science at UM" Grants Program

Brooke M. Crawford, MD MBA

Associate Professor and Chief, Division of Orthopaedic Oncology
Associate Program Director, Orthopaedic Surgery Residency
UNIVERSITY OF MIAMI
Leonard M. Miller School of Medicine
Department of Orthopaedics

“Using deep-learning model to improve the accuracy of pathologic fracture prediction in breast and prostate cancer patients with metastases to bone”

Firdaus S. Dhabhar, PhD

Tenured Professor
Director, Scholarly Concentrations—Advances in Mind-Body Medicine
UNIVERSITY OF MIAMI
Leonard M. Miller School of Medicine
Department of Psychiatry and Behavioral Sciences

“Digital Well-Being Coaching for Medical Students”

Adam Meyers, PhD, Fall 2025 IDSC Grant Awardee, University of Miami Frost Institute for Data Science and Computing "Expanding the Use of Collaborative Data Science at UM" Grants Program

 

Adam Meyers, PhD

Assistant Professor
UNIVERSITY OF MIAMI
College of Engineering
Department of Industrial and Systems Engineering

“Deep Learning-Based Statistical Process Control for Improving the Efficiency of Surgical Operating Room Centers”

Tatjana Rundek, MD PhD, Fall 2025 IDSC Grant Awardee, University of Miami Frost Institute for Data Science and Computing "Expanding the Use of Collaborative Data Science at UM" Grants Program

Tatjana Rundek, MD PhD

Professor of Neurology
Evelyn F. McKnight Chair for Learning and Memory in Aging
Scientific Director, Evelyn F. McKnight Brain Institute
Executive Vice Chair, Research and Faculty Affairs, Dept. of Neurology
Director, Clinical Translational Research Division (CTRD)
Director, Master of Science in Clinical Translational Investigations
UNIVERSITY OF MIAMI
Leonard M. Miller School of Medicine
Department of Neurology | Clinical Translational Research Division (CTRD)

“Clinically Interpretable AI Model for Precision Risk Stratification in Alzheimer’s Disease Progression”

Shirin Shafazand, MD MS FABSM ATSF, Fall 2025 IDSC Grant Awardee, University of Miami Frost Institute for Data Science and Computing "Expanding the Use of Collaborative Data Science at UM" Grants Program

Shirin Shafazand, MD MS FABSM ATSF

Professor of Clinical Medicine
UNIVERSITY OF MIAMI
Leonard M. Miller School of Medicine
Department of Medicine | Division of Pulmonary, Critical Care, and Sleep Medicine

“Screening Women For Obstructive Sleep Apnea Using the Electronic Health Record: A Machine Learning Approach”