MIDAS’s research centers build on the expertise of U-M faculty, focusing on innovative data science tools and methodologies.

Center for Data-Driven Transportation Research

The Next Generation of Mobility

The mission of the Center for Data-Driven Transportation Research is to harness the power of big data to help develop the next generation of mobility, from driverless and autonomous vehicles to integrated multi-modal transportation systems. The center is partially funded by the $100 million Data Science Initiative, which, among other efforts, provides faculty research grants for projects likely to garner significant investment from industry or government.

Center for Data-Intensive Learning Analytics Research

Improving education through data

The Center for Data-Intensive Learning Analytics Research helps U-M faculty take advantage of the trove of student data collected by the University over the years to improve educational practices and student outcomes, and is partially funded by the $100 million Data Science Initiative.

Center for Data-Intensive Health Science Research

Advancing the spectrum of biomedical research

The Center for Data-Intensive Health Science Research aims to enhance U-M biomedical researchers’ ability embrace the opportunities and challenges brought about by advances in data science. The center will catalyze the development of theories and innovative methodologies in data science, and their application to the entire spectrum of biomedical science, from basic research to translation research, to clinical applications, with the ultimate goal of using data science to improve the health of our society.

Center for Data-Intensive Social Science Research

Leading the evolution of social research

The data science revolution is bringing unprecedented opportunities to social science research.  Never before have we had such enormity and variety of data, from endless social media streams to every survey imaginable, from outputs of every conceivable sensor and wireless device to massive consumer databases. We are seeing data in every form, every level of granularity and quality.  Social scientists’ newest challenge is to generate insight from the data for the political, economic and social wellbeing of individuals and our society.

Research Highlights

Workshop co-chaired by MIDAS co-director Prof. Hero releases proceedings on inference in big data

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The National Academies Committee on Applied and Theoretical Statistics has released proceedings from its June 2016 workshop titled “Refining the Concept of Scientific Inference When Working with Big Data,” co-chaired…

MIDAS announces second round of Data Science Challenge Initiative awards, in health and social science

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Five research projects — three in health and two in social science — have been awarded funding in the second round of the Michigan Institute for Data Science Challenge Initiative…

$800,000 in awards for data science projects in partnership with Shanghai Jiao Tong University

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With input from MIDAS, four research teams from the University of Michigan and Shanghai Jiao Tong University in China are sharing $800,000 in awards to study depression, electric vehicles, urban…

Research highlights: U-M group awarded Midwest Big Data Spoke award from NSF for Advanced Computational Neuroscience Network (ACNN)

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A group of three University of Michigan faculty members will lead the Advanced Computational Neuroscience Network project as a “spoke” in the Midwest Big Data Hub program funded by the…