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
A paper by members and faculty leaders of the Michigan Data Science Team (co-authors: Jacob Abernethy, Alex Chojnacki, Arya Farahi, Eric Schwartz, and Jared Webb) won the Best Student Paper…
The University of Michigan is part of an NSF-supported 17-university coalition dedicated to creating next-generation computing power to support high-energy physics research. Led by Princeton University, the Institute for Research…
MIDAS-supported researchers recently demonstrated an algorithm-based system that works better than humans in identifying fake news stories. Press release | Paper presented to the 27th International Conference on Computational Linguistics…
MIDAS-supported researchers recently published a paper on the potential for incorporating ridesourcing services with public transit. Press release | Paper in Transportation Research
A paper by members and faculty leaders of the Michigan Data Science Team (co-authors: Jacob Abernethy, Alex Chojnacki, Arya Farahi, Eric Schwartz, and Jared Webb) won the Best Student Paper…
The University of Michigan is part of an NSF-supported 17-university coalition dedicated to creating next-generation computing power to support high-energy physics research. Led by Princeton University, the Institute for Research…
Description: Engineers are encountering and generating a ever-growing body of data and recognizing the utility of applying data science (DataSci) approaches to extract knowledge from that data. A common barrier to…
The University of Michigan has been recognized as one of the first Chapters in the new Women in High Performance Computing (WHPC) Pilot Program. “The WHPC Chapter Pilot will enable…
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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 awarded in Spring 2018
The Data Science for Music Challenge Initiative distributed four, one-year grants of $75,000 each for research projects at the intersection of music and data science.
