U-M Announces $100 Million Data Science Initiative

U-M Announces $100 Million Data Science Initiative

Last week, the University of Michigan announced a big, new public-private initiative similar to its Mobility Transformation Center—only this time, the focus is on big data and the ever-improving technologies to gather, store, search, and analyze large collections of information.

The $100 million Data Science Initiative (DSI) will establish the Michigan Institute for Data Science (MIDAS) to lead research and education as well as collaborate with industry—with a particular focus on the automotive, advanced manufacturing, chemical, finance, healthcare, and pharmaceutical sectors.

The goals of the DSI include better training for faculty and students in cutting-edge new methods of data science, expanding the university’s research computing capacity, and bolstering U-M’s data management, storage, and analytics resources.

Another component of the DSI will be a “bottom-up faculty engagement process,” according to MIDAS co-director Brian Athey. To spur faculty innovation, U-M has launched the Challenges Initiatives Program, which seeks to bring data scientists together with experts in transportation research, learning analytics, personalized medicine, and social science to solve real-world problems.

For example, Athey says, in one project with U-M’s Mobility Transformation Center, researchers are collecting a continuous stream of data from nearly 3,000 private cars, trucks, and buses on the streets of Ann Arbor in order to test the way connected vehicles operate. The DSI will help parse the huge amount of data being generated even as the number of vehicles expands to more than 20,000.

Other applications Athey imagines for DSI research includes using big data to boost the effectiveness of biomedical and health research and get technological advances to market faster, or analyzing massive amounts of social media data as a way to better understand a broad range of socioeconomic issues.

“The plan is to launch these four challenges over three years and add more going forward,” Athey says. “We want to target faculty across campus as well as data science experts. If our intellectual capital is aligned, it will enable our activities to flourish.”

Athey plans to emulate the Mobility Transformation Center—which has an impressive roster of companies that have ponied up money to participate in research projects—when it comes to inviting industry to join in the DSI’s efforts.

“We’re anxious to build new kinds of big data partnerships with corporate partners,” he adds. (Those in the private sector interested in collaborating with the DSI should contact U-M’s Business Engagement Center at [email protected].)

Al Hero, MIDAS co-director, says it will be critical to train college students in data science as the Internet of Things takes root and scientists have access to reams of data, along with new techniques to analyze it.

“We need to develop curricula and continuing education mechanisms for a new generation of data science students,” he says. “When you look at the computer science workforce, there’s a large percentage of students who haven’t studied data science formally. We’re hoping industry will help shape our data science education programs.”

An inaugural symposium will be held at U-M’s Rackham Amphitheater on Oct. 6 to celebrate the launch of the DSI; it’s free and open to the public. Athey says a host of corporate partners will be on hand to discuss their involvement in the DSI initiative, including GM, Ford, IBM, Barracuda Networks, and Intel.

“I’ve been at the university for 30 years, and I’ve never seen anything quite like this,” says Athey, who also notes that though there are other, similar big data projects—he mentions the Center for Data Science at New York University and the Data Science Institute at Columbia University—there’s nothing he considers quite this ambitious. “Across the nation, this is one of the largest initiatives of its kind at any university, and it will definitely impact the transition of these technologies to the marketplace,” he says. “We’ve hit a tipping point in terms of what data touches: every area of science and technology.”

Share the Article