# Big Data Health Science Scholar Program for Infectious Diseases

> **NIH NIH T35** · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · 2022 · $155,576

## Abstract

Abstract
Today, a critical mass of previously collected linked health care data is now available for
optimizing patient health outcomes. Information, insights, and intelligence existing in such health
care data can be unlocked efficiently using Big Data Science (BDS).As people age and live
longer, increased demand for care will be two-fold, one for those living with more comorbidities,
and second the emergent risks from new infectious diseases like COVID-19.The recent NIAID
strategic plan for COVID-19 highlights the urgent and important need for high-quality scientific
research to improve knowledge around disease transmission, surveillance, and its impact on
health outcomes, and to develop both biomedical and public health measures to mitigate illness
and death. The existence of several massive, and information rich big data streams in
healthcare (e.g., electronic health records [EHR], mobile technologies, wearable devices,
genomic data, geospatial data etc.) and the advances in information and computational
technologies (e.g., machine learning and artificial intelligence) now offer an excellent hands-on
training opportunity for applying innovative Big Data science (BDS) research to infectious
diseases such as HIV/AIDS and COVID-19. To cultivate a thriving and talented pipeline of next
generation scientists, it is essential to engage current students early and provide new and
innovative training opportunities to generate interest in the biomedical, social, and behavioral,
and clinical sciences. Therefore, we propose offering a 10-week Short-Term Summer Research
Training Program titled “Big Data Health Science Scholar Program for Infectious Diseases”
targeted towards predoctoral students in physical and/or quantitative sciences (departments of
biomedical engineering, integrated information technology, chemistry/biochemistry,
mathematics, statistics etc.) from across South Carolina (SC) and the United States (US).
Predoctoral students completing this training will engage in experiential learning through hands-
on research in infectious disease areas like HIV/AIDS, and COVID-19, both relevant to the
NIAID mission. Selected predoctoral students will be paired with Program Faculty mentors from
a pool of distinguished participating faculty for one-on-one mentoring. Trainees will be chosen
through a competitive process based on their proposed research plan and goals for the summer
experience. Specifically, we plan to recruit 8 predoctoral students from physical and quantitative
sciences across the US per year (a total of 40 over the entire funding period) to participate in
the 10-week summer intensive training program with the following objectives:
Objective 1: Create a summer big data science training pipeline for qualified predoctoral
students by exposing them to relevant courses/training for competency development in the
application of BDS to infectious disease research.
Objective 2: Engage trainees in hands-on research using HIV and COVID-19 data.
O...

## Key facts

- **NIH application ID:** 10487564
- **Project number:** 5T35AI165252-02
- **Recipient organization:** UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
- **Principal Investigator:** Neset Hikmet
- **Activity code:** T35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $155,576
- **Award type:** 5
- **Project period:** 2021-09-10 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10487564

## Citation

> US National Institutes of Health, RePORTER application 10487564, Big Data Health Science Scholar Program for Infectious Diseases (5T35AI165252-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10487564. Licensed CC0.

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