MIDAS Research Hubs

Building on the expertise of U-M faculty,
focusing on innovative data science tools and methodologies.

MIDAS Research Hub: Transportation

The Next Generation of Mobility

The mission of the MIDAS Transportation Research Hub 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 Hub is partially funded by the U-M Data Science Initiative, which, among other efforts, provides faculty research grants for projects likely to garner significant investment from industry or government.

MIDAS Research Hub: Health Science

Advancing the spectrum of biomedical research

The MIDAS Health Science Research Hub aims to enhance U-M biomedical researchers’ ability embrace the opportunities and challenges brought about by advances in data science. The Hub 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.

MIDAS Research Hub: Learning Analytics

Improving education through data

The MIDAS Learning Analytics Research Hub 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 U-M Data Science Initiative.

MIDAS Research Hub: Social Science

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.

MIDAS Research Hub: Music

Connecting data science and music

U-M has incredible depth in data science expertise and a world-class School of Music, Theatre and Dance.  With this initiative, MIDAS helps U-M scientists lead the nation the research at the intersection of data science and music.

Research and Publications
In the News

See a complete listing of publications from MIDAS-affiliated faculty via Google Scholar.

MIDAS researchers’ papers accepted at ACM KDD data science conference in London

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Several U-M faculty affiliated with MIDAS will participate in the KDD2018 Conference in London in August. The meeting is held by the Associate for Computing Machinery's Special Interest Group in…

Dinov article: Building consensus on data science education and training

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Dr. Ivo Dinov, professor of Computational Medicine and Bioinformatics, Human Behavior, and Biological Science, and associate director of MIDAS, recently published an article on the training and education curricula needs…

Deep learning in pharmacogenomics: from gene regulation to patient stratification

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MIDAS-affiliated researchers recently published a review of current and future applications of deep learning in pharmacogenomics. Title: Deep learning in pharmacogenomics: from gene regulation to patient stratification Published in: Pharmacogenomics, April…

U-M, MIDAS researchers supported by Chan Zuckerberg Initiative

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Several University of Michigan researchers, including faculty affiliated with MIDAS, recently received support from the Chan Zuckerberg Initiative under its Human Cell Atlas project. The project seeks to create a…

Paper on the impact of mode sharing on sentiment using geosocial media data accepted for publication by Journal of Location-Based Services

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A paper by lead author Greg Rybarczyk, Associate Professor of Geography and GIS at U-M Flint, and Syagnik Banerjee, Associate Professor of Marketing at UM-Flint, has been accepted for forthcoming…

MIDAS Data Science for Music Challenge Initiative announces funded projects

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From digital analysis of Bach sonatas to mining data from crowdsourced compositions, researchers at the University of Michigan are using modern big data techniques to transform how we understand, create…