Novel Biostatistical, Epidemiologic, and Machine Learning Methods Awards
These awards support the development of novel biostatistical, epidemiologic, and machine learning methods in translational science designed to address fundamental challenges and barriers that are common to translational research and health equity across diseases and health conditions. A Maximum of $25,000 will be awarded for a one-year period.
Return to: Funding Directory
Eligibility
All faculty members with a primary appointment at the University of Rochester are eligible to serve as principal investigators. Co-investigators may be from institutions other than the University of Rochester. Investigators who have received a Novel Biostatistical and Epidemiologic Methods award in the prior two years are not eligible to apply.
Funding Amount
These awards provide up to $25,000 over one year.
Important Dates
- Letters of intent due – January 6, 2025 at 5 p.m.
- Notification of full proposal invitations – February 10, 2025
- Full proposals? due – March 24, 2025 at 5 p.m.
- Notifications of award? – May 28, 2025
- Anticipated start date – July 1, 2025
Note: All animal and human subject protocols must be approved by NCATS, the NIH institute funding the UR CTSI, prior to the start date. No funds for research project costs may be released until all required human subjects and animal welfare approvals have been received.
Contact
General Inquiries
Mary Little - mary_little@urmc.rochester.edu
Biostatistics or Epidemiology Scientific and Peer Review Questions
Robert Strawderman, ScD - robert_strawderman@urmc.rochester.edu
Edwin van Wijngaarden, PhD - edwin_van_wijngaarden@urmc.rochester.edu
Informatics, Artificial Intelligence, or Machine Learning Questions
Dongmei Li - dongmei_li@urmc.rochester.edu
Financial Questions
Mary Lyons - mary_lyons@urmc.rochester.edu
Apply
Solicitation and Review Process
Phase 1: Applicants submit a two-page letter of intent stating their specific aims and summarizing their proposals. The UR CTSI review committee specific to each submission category will evaluate, score, and discuss the letters of intent.
Phase 2: A subset of applicants will be invited to submit full proposals. The UR CTSI Review Committee specific to each submission category will engage in a formal study section-style discussion and scoring meeting for proposals, or proposals will be reviewed by experts at another CTSA Program institution through an exchange program. Funding recommendations go to the UR CTSI Executive Team for a final review and decision on funding.
- View the 2025 RFA for the NBEMM Pilot Award.
- The NBEMM Funding Attestation must be submitted with the initial letter of intent and full proposal.
- View the NBEMM Letter of Intent Template.
Scholars and Projects
Current Projects
Modeling neural responses to natural sounds using component-encoding models
Samuel Norman-Haignere, Ph.D.
Assistant Professor of Biostatistics and Computational Biology, Biomedical Engineering, and Neuroscience
Awarded in 2023
Past Projects
Differential abundance analysis of microbiota conditional on their functional difference
Michael Sohn, Ph.D.
Assistant Professor of Biostatistics and Computational Biology
Statistical methods to quantify imaged microglia
Matthew McCall, Ph.D. Biostat Bio
Associate Professor of Biostatistics
Inference on human populations from single cell transcriptional profiling
Andrew McDavid, Ph.D.
Assistant Professor of Biostatistics and Computational Biology
Machine learning based mediation analysis: Application in a study of birth weight
Ashkan Ertefaie, Ph.D.
Assistant Professor of Biostatistics and Computational Biology
Personalized medical image Analysis Based on Partial Differential Equations
Xing Qiu, Ph.D.
Associate Professor of Biostatistics and Computational Biology
Estimation of cell-type specific microRNA expression in complex tissue samples
Matthew McCall, Ph.D.
Assistant Professor of Biostatistics and Biomedical Genetics
Development of a Clinical Trial Simulation Tool for Huntington's Disease
Charles Venuto, PharmD
Assistant Professor of Neurology in the Center for Health and Technology
Development of qPCR methodology for clinical testing
Matthew McCall, Ph.D.
Assistant Professor of Biostatistics and Biomedical Genetics
Weighted Functional Gene Set Enrichment Analysis for Time-course Transcriptome Studies
Xing Qiu, Ph.D.
Associate Professor of Biostatistics and Computational Biology
Novel models for analyzing drinking outcomes: A pilot study comparing competing approaches
Hua He, Ph.D.
Assistant Professor, Biostatistics and Computational Biology
Detecting Intergene Association Changes in Microarray Data
Rui Hu, Ph.D.
Research Assistant Professor, Biostatistics and Computational Biology
Integrative Analysis of Pathways to SA and PPD in High Risk Families
Yinglin Xia, Ph.D., M.S.
Research Assistant Professor, Biostatistics and Computational Biology
Clustering Differentially Associated Genes
Rui Hu, Ph.D.
Research Assistant Professor of Biostatistics and Computational Biology
Co-Investgators: Sandhya Dwarkadas, PhD, Galina Glazko, PhD, Xing Qiu, PhD
Parameter estimation for nonlinear stochastic differential equation models from noisy longitudinal data in HIV dynamic research
Hongqi Xue, Ph.D.
Research Assistant Professor of Biostatistics and Computational Biology