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
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…
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…
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…
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…
