# Big Data Health Science Fellow Program in Infectious Disease Research

> **NIH NIH R25** · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · 2021 · $350,996

## Abstract

Abstract
The multiple, massive, and rich Big Data streams in healthcare (e.g., electronic health records, mobile
technologies, wearable devices, genomic data) and the emergence of advanced information and computational
technologies (e.g., machine learning and artificial intelligence) offer an invaluable opportunity for applying
innovative Big Data science research in NIAID focus areas of infectious diseases such as HIV/AIDS and
COVID-19. Big Data science has the potential to identify high-risk individuals and communities and prioritize
them for early biomedical or public health interventions, predict long-term clinical outcomes and disease
progression, and evaluate public health policy impact. Key to addressing these complexities is a critical mass
of health researchers with adequate knowledge, competencies, and skills to unlock important answers from Big
Data to better understand, treat, and ultimately prevent these diseases and related comorbidities. However,
there is a nationwide shortage of talent with such knowledge, competencies, and skills, especially in traditional
academic settings. While junior faculty, as part of the generations of digital learners, have the greatest potential
to develop their Big Data health science research agenda, many face multiple structural barriers to conduct Big
Data science research. Such barriers include a lack of protected time to initiate new interdisciplinary Big Data
research, lack of opportunity to participate in funded Big Data research, and a lack of adequate mentoring. To
address these gaps, we propose developing a “Big Data Heath Science Fellow” program for early career junior
faculty (i.e., assistant professors) at health science schools (e.g., medicine, public health, nursing, pharmacy,
social work) at the University of South Carolina (USC). Specifically, we plan to recruit 4 USC health science
junior faculty per year and provide them with protected time (25%) to participate in the comprehensive training
program, including: 1) courses for competency and skill development in Big Data research and professional
development; 2) participation in hands-on research and grant proposal development; and 3) rich mentoring
experience in Big Data research and professional development. The proposed training program will be
implemented with the support of the existing infrastructure of the USC Big Data Health Science Center
(BDHSC), one of USC’s Excellence Initiatives. BDHSC’s mission is to promote and support Big Data health
science research at USC and across SC through capacity development, academic training, professional
development, community engagement, and methodological advancement. BDHSC contains 5 content cores
(electronic health records, geospatial, genomic, social media, and bio-nanomaterial data) and 2 supporting
hubs (business/entrepreneurship and technology) with the involvement of 43 faculty from 10 USC
college/schools. The proposed training will be an integral component of the BDHSC professional d...

## Key facts

- **NIH application ID:** 10311679
- **Project number:** 1R25AI164581-01
- **Recipient organization:** UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
- **Principal Investigator:** Xiaoming Li
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $350,996
- **Award type:** 1
- **Project period:** 2021-08-04 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10311679

## Citation

> US National Institutes of Health, RePORTER application 10311679, Big Data Health Science Fellow Program in Infectious Disease Research (1R25AI164581-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10311679. Licensed CC0.

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