Michigan is home to a new institute that aims to facilitate finding the gold nuggets in the massive data sets now available to researchers in virtually all fields. Called the Michigan Institute for Data Science (MIDAS), it is the new focal point for the multidisciplinary discipline of data science at Michigan, and part of Michigan’s $100M Data Science Initiative.
“The affiliations of the more than 120 faculty involved so far gives an insight into the breadth of activity that falls under Data Science,” said Al Hero, R. Jamison and Betty Williams Professor of Engineering, and newly-named co-director of MIDAS. “They include the College of Engineering, the Medical School, the College of Literature, Sciences and the Arts, the School of Public Health, the School of Information, in addition to other units such as the Institute for Social Research, Nursing, Business, School of Natural Resources, Transportation Research Institute, and the Michigan Census Research Data Center.”
The key mission of MIDAS is to facilitate shared knowledge and synergy among those already working in the area of Data Science, with the goal of advancing technologies and scientific methods that can be used in a wide variety of applications.
At Michigan, faculty have access to massive data sets related to their own research in areas as diverse as: public health and personalized medicine; transportation with connected vehicles; brain sciences; environmental and earth sciences; astronomy; materials science; genomics and proteomics; computational social science; business analytics; learning analytics; computational finance; information forensics; and national defense. At the same time, researchers are dealing with critical associated issues such as high-performance computation and cyber security.
“There’s an immense amount of data generated from sensing devices and other sources,” said Prof. Hero, “yet very little scientific methodology available to merge this data into usable information.” As a discipline, data science lies at the intersection of mathematics, statistics, computer science, information science, and engineering.
Prof. Hero, with appointments in Electrical Engineering and Computer Science, Biomedical Engineering, and Statistics, and research specialties in statistical signal and image processing, machine learning, and data mining, is uniquely qualified to take on the role as co-director in this critical early phase of the Institute. His research has applications in health, materials science, security and defense, medical imaging, as well as sensor network tracking and localization. He has received several best paper awards in several different professional conferences during the past three decades; he authored the book, Foundations and Application of Sensor Management(Springer 2008); and he is director of the MURI, Value-centered information theory for adaptive learning, inference, tracking, and exploitation.
In addition, Prof. Hero has been a leader in the professional community, sitting on the Board of Directors of IEEE as Director of Division IX (Signals and Applications), serving as President of the IEEE Signal Processing Society, and serving as the Digiteo Chaire d’Excellence at the Digiteo Research Park in Information Science and Technology, Paris, France.
Prof. Hero is looking forward to applying his analytical and organizational expertise to MIDAS:
“It’s very exciting for me to help move the extraordinary and diverse activities happening in the field of data science at Michigan into a more coordinated focus. I want to enhance the data science community in terms of collaboration (which has always been of tremendous value in my own research), access to resources, and the identification of new directions for funding with the goal of improving the overall scientific enterprise.”
Co-directing MIDAS is Prof. Brian Athey, Michael A. Savageau Collegiate Professor and Chair, Computational Medicine and Bioinformatics (DCM&B). Prof. Athey is also a Professor of Psychiatry and Internal Medicine, and a national leader in translational biomedical informatics.
MIDAS is part of U-M’s Advanced Research Computing (ARC), which houses advanced computing resources to enable data-intensive and computational research.
October 6, 2015 – RSVP
Primary MIDAS activity
Education and training
- New undergraduate program and graduate-level certificate in data science
- Continuing education for alumni
- Industry-sponsored projects
Research and Collaboration
$10M in funding available in the areas of:
- Learning Analytics
- Computational Social Science
- Health Sciences
- High-performance computing
EECS Faculty Involved in MIDAS
Mike J. Cafarella
H. V. Jagadish
Emily Mower Provost
Raj Rao Nadakuditi
Dragomir R. Radev
Martin J. Strauss
Related Article: U-M launching $100 million Data Science Initiative, September 8, 2015, The University Record.
Posted September 8, 2015