The Michigan Institute for Data Science (MIDAS) catalyzes data science at the University of Michigan through support for faculty, research, education and training, and industry engagement.

WHAT’S NEW

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…

STATCOM featured in American Statistical Association magazine

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The U-M Statistics in the Community (STATCOM) group was recently featured in AMSTATNEWS, the magazine of the American Statistical Association. Read the article at https://magazine.amstat.org/blog/2018/04/01/statcom-universities/. STATCOM is supported in part by…

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…

CASC image competition open for submissions

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The image competition for the Coalition for Academic Scientific Computation (CASC) 2019 annual brochure is now open. Winning images will be featured in the brochure, which is distributed to industry,…

ARC-TS joins Cloud Native Computing Foundation

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Advanced Research Computing - Technology Services (ARC-TS) at the University of Michigan has become the first U.S. academic institution to join the Cloud Native Computing Foundation (CNCF), a foundation that…

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RT @brockpalen:#linux #HPC #job with #cloud join a large team of HPC professionals and help them take HPC computing to the cloud!… https://t.co/JMuUik3lit 
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SAVE THE DATE: Monday, Aug. 6, 2nd annual MIDAS symposium on Single Cell Data Analytics Info:… https://t.co/Jvx5KMBfNg 
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RT @michigan_AI:Congratulations to Prof. @emilymprovost for the tenure and promotion! So well deserved! 👏 https://t.co/MZOfTp7HZ1 https://t.co/mWHGZDu0jF 

MIDAS Highlights

MIDAS working groups foster cross-disciplinary collaboration

Focus on funding opportunities or research themes

MIDAS regularly convenes research working groups, bringing together investigators from various fields to work on shared research issues or pending funding opportunities.

Subjects include Data Integration, Mobile Sensor Analytics, Teaching Data Science, Trustworthy Data Science.

For more information or to suggest a topic for a new group, contact Jing Liu, MIDAS Senior Scientist (ljing@umich.edu; 734-764-2750).

MIDAS seeks candidates for faculty positions

The University of Michigan, Ann Arbor, seeks candidates for multiple full-time tenured or tenure-track faculty positions in the field of data science. The positions are open to candidates at all ranks and both methodological and applied areas of data science will be considered. The University is especially interested in candidates whose research interests lie in data science methodology and its application to transportation, learning analytics, personalized health and precision medicine, or computational social science.

Video, slides available from 2017 MIDAS symposium

“A Data-Driven World: Potentials and Pitfalls”

The MIDAS Annual Symposium, “A Data-Driven World: Potential and Pitfalls,” took place October 11, 2017, in Rackham Auditorium and the Michigan League. The symposium featured prominent researchers whose work is on the leading edge of innovation and discovery in data-intensive science, as well as a poster competition highlighting data science research at U-M.

Data Acquisition for Data Science

Data Acquisition for Data Science (DADS) supports acquisition, preparation, management, and maintenance of specialized research data sets used in current and future data science-enabled research projects across U-M, with special focus on the four challenge initiative areas pursued by MIDAS: transportation science, health science, social science, and learning analytics.

Forum features data science research at U-M

Presentations and posters from across campus

Interdisciplinary research, collaboration with industry, and taking advantage of the computational resources available at Michigan were some of the themes of the MIDAS Research Forum held in December 2017.

The keynote talk was given by Christopher J. Rozell, Associate Professor, Electrical and Computer Engineering, Georgia Institute of Technology.

Data Science for Music

Funding awards in Spring 2018

The Data Science for Music Challenge Initiative will award four, one-year  grants of up to $75,000 each for research projects at the intersection of music and data science.