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

University of Michigan researcher contributes to NASA findings on carbon in the atmosphere showcased in the journal Science

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  High-resolution satellite data from NASA’s Orbiting Carbon Observatory-2 are revealing the subtle ways that carbon links everything on Earth – the ocean, land, atmosphere, terrestrial ecosystems and human activities….

Winning posters from 3rd Annual MIDAS Symposium

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More than 50 students took part in the Student Poster Competition during the 3rd Annual MIDAS Symposium. The winning entries can be viewed at http://midas.umich.edu/2017-symposium/winning-posters/

Real estate dataset available to researchers

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The University of Michigan Library system and the Data Acquisition for Data Sciences program (DADS) of the U-M Data Science Initiative (DSI) have recently joined forces to license a major…

MDST Partners with City of Detroit to Improve Blight Enforcement

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Author: Allie Cell, College of Engineering PROBLEM OVERVIEW Property blight, which refers to lots and structures not being properly maintained (as pictured above), is a major problem in Detroit: over…

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MIDAS Highlights

Celebrating Claude Shannon, the Father of Information Theory

The University of Michigan is celebrating the 100th birthday of Claude E. Shannon, a U-M alum widely recognized as the father of information theory, with a Shannon Centennial Symposium on Sept. 16, 2016, and a biweekly Shannon Centennial Lecture Series during the fall 2016 semester.

Building a Community of Social Scientists with Big Data Skills

As the use of data science techniques continues to grow across disciplines, a group of University of Michigan researchers are working to build a community of social scientists with skills in Big Data through a week-long summer camp for faculty and graduate students.

Video, slides available from 2016 MIDAS symposium

“Advancing Science, Changing the World”

Top data scientists from around the country gathered in Ann Arbor for the second annual MIDAS symposium. The event featured U-M faculty presenting information on projects that received funding through the MIDAS Challenge Initiative, and a student poster session.

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.

Al Hero named Distinguished Professor

One of nine honored in spring 2016

MIDAS Co-Director, Prof. Alfred Hero III, was named a 2016 Distinguished University Professor, the University of Michigan’s top honor bestowed on faculty by the Board of Regents.  Professor Hero is now John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science, and R. Jamison and Betty Williams Professor of Engineering, professor of electrical engineering and computer science, College of Engineering; professor of biomedical engineering, CoE and Medical School; and professor of statistics, LSA.

U-M plays leading role in regional big data hub

NSF effort to catalyze data science research

A “big data brain trust” has been established by the National Science Foundation to bring together industry, government and academia to accelerate this emerging field and harness it to solve some of society’s toughest problems.

The University of Michigan will play a leading role in the new Midwest Big Data Innovation Hub—one of four that NSF has set up across the nation. U-M is one of five universities that will lead the Midwest hub. Professor Brian Athey, co-director of U-M’s Michigan Institute for Data Science, will lead the effort at U-M.