# Transforming Analytical Learning in the Era of Big Data

> **NIH NIH R25** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2021 · $250,974

## Abstract

PROJECT SUMMARY
In this dawning era of `Big Data' it is vital to recruit and train the next generation of biomedical data scientists in
`Big Data'. The collection of `Big Data' in the biomedical sciences is growing rapidly and has the potential to solve
many of today's pressing medical needs including personalized medicine, eradication of disease, and curing
cancer. Realizing the benefits of Big Data will require a new generation of leaders in (bio)statistical and
computational methods who will be able to develop the approaches and tools necessary to unlock the information
contained in large heterogeneous datasets. There is a great need for scientists trained in this specialized, highly
heterogeneous, and interdisciplinary new field of health big data. Thus, the recruitment of talented
undergraduates in science, technology, engineering and mathematics (STEM) programs is vital to our ability to
tap into the potential that `Big Data' offers and the challenges that it presents.
The University of Michigan Undergraduate Summer Institute: Transforming Analytical Learning in the Era of
Big Data will primarily draw from the expertise and experience of faculty from three different departments within
three different schools at the University of Michigan: Biostatistics in the School of Public Health, Computer
Science in the School of Engineering, Statistics in the College of Literature, Sciences and the Arts. The faculty
instructors and mentors have backgrounds in Statistics, Computer Science, Information Science, Medicine,
Population Health, Social and Biological Sciences. They have active research programs in a broad spectrum of
methodological areas including statistical modeling, data mining, natural language processing, statistical and
machine learning, large-scale optimization, matrix computation, medical computing, health informatics, high-
dimensional statistics, distributed computing, missing data, causal inference, data management and integration,
signal processing and medical imaging. The diseases and conditions they study include obesity, diabetes,
cardiovascular disease, cancer, neurological disease, kidney disease, injury, macular degeneration and
Alzheimer's disease. The areas of biology include neuroscience, genetics, genomics, metabolomics, epigenetics
and socio-behavioral science. Undergraduate trainees selected will have strong quantitative skills and a
background in STEM. The summer institute will consist of a combination of coursework, to raise the skills and
interests of the participants to a sufficient level to consider pursuing graduate studies in `Big Data' science, along
with an in depth mentoring component that will allow the participants to research a specific topic/project utilizing
`Big Data'. We have witnessed tremendous enthusiasm and success with the current summer program on Big
Data led by this team with 164 students trained in the last 4 years (2015-2018) including 90 female students
and 30 students from underrepresented m...

## Key facts

- **NIH application ID:** 10130608
- **Project number:** 5R25HL147207-03
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Jian Kang
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $250,974
- **Award type:** 5
- **Project period:** 2019-03-15 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10130608

## Citation

> US National Institutes of Health, RePORTER application 10130608, Transforming Analytical Learning in the Era of Big Data (5R25HL147207-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10130608. Licensed CC0.

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