This project from the University of Louisville Research Foundation will support acquisition of a Big Data Analysis Platform (BDAP) with high performance data storage, networking, and processing capabilities. The platform will support research in multimedia, biomedicine, metagenomics, and health data analysis. In addition, the platform will allow general research on efficient management and analysis of big data. Moreover, strengthening scientific research across the university, the researchers will engage with K-12 students and teachers.

The project will advance the state-of-the-art in big data management and analysis by enabling five research thrusts that will use the BDAP equipment purchased by this award. First, BDAP will provide improvement over existing big data management techniques by introducing self-optimizing and energy efficient big data platforms through dynamic data placement, retrieval, and reorganization algorithms, as well as enabling efficient big data analysis through novel heterogeneous and multi-source data clustering algorithms. Second, BDAP will allow experimentation with novel algorithms guided by deep neural networks to analyze big multimedia data. Third, BDAP will enable experimentation with new paradigms for integrating big biomedical data from multiple sources including image, genomic, quantitative, biological, and observational data. Fourth, BDAP will enable testing of techniques to generate, store, analyze and integrate large microbiome, health and socioeconomic data sets to determine the causal relationship between specific microbial profiles and human health via bioinformatics and data mining approaches. Finally, the project will contribute to the development of new statistical methods for analyzing high dimensional data for epigenetic, pharmacogenomics, and genome association studies. This in-house instrument enables energy consumption measurements and permanent storage for sensitive data sets of petabyte-range. While advancing engineering knowledge, the instrumentation supports computational, statistical, and bioengineering research, that applies engineering principles to several problems in biology and medicine.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
1828521
Program Officer
Rita V. Rodriguez
Project Start
Project End
Budget Start
2018-10-01
Budget End
2020-09-30
Support Year
Fiscal Year
2018
Total Cost
$478,727
Indirect Cost
Name
University of Louisville Research Foundation Inc
Department
Type
DUNS #
City
Louisville
State
KY
Country
United States
Zip Code
40202