Skip to main content

University of Michigan launches big data initiative

The University of Michigan (U-M) plans to invest US$100 million over the next five years in a new data science initiative aimed at working with big data sets that can further research into such things as driverless cars, medicine and climate change. The money will pay for 35 new faculty members to be hired over the next four years, support interdisciplinary data-related research initiatives and foster new methodological approaches to big data, as well as enabling the university to expand its research com
September 9, 2015 Read time: 2 mins
The University of Michigan (U-M) plans to invest US$100 million over the next five years in a new data science initiative aimed at working with big data sets that can further research into such things as driverless cars, medicine and climate change.

The money will pay for 35 new faculty members to be hired over the next four years, support interdisciplinary data-related research initiatives and foster new methodological approaches to big data, as well as enabling the university to expand its research computing capacity.

In one project at U-M's Mobility Transformation Center, for example, researchers are collecting a continuous stream of data at a rate of ten times per second from each of nearly 3,000 private cars, trucks and buses on the streets of Ann Arbor in order to test the operation of connected vehicles. The DSI will help collect, store and analyse the huge amount of data being generated even as the number of vehicles expands to more than 20,000.

The university is also carrying out research in medicine And public health, teaching and learning, and social science.

"Big data can provide dramatic insights into the nature of disease, climate change, social behaviour, business and economics, engineering, and the basic biological and physical sciences," said U-M President Mark Schlissel. "With our widely recognised strengths across all of these areas and our longstanding culture of collaboration across disciplines, U-M is in a unique position to leverage this investment in data science for the good of society."

"Big data is revolutionising research in an extraordinary range of disciplines," said S. Jack Hu, interim vice president for research. "With this initiative, our goal is to spark innovation in research across campus while inspiring further advances in the techniques of data science itself."

Related Content

  • Align transport infrastructure needs with ITS offerings
    July 19, 2012
    Kallistratos Dionelis, General Secretary of ASECAP, ponders the absence of creativity and innovation in the road management sector. 'Traditional' road managers and ITS specialists share many of the same ultimate goals and yet, he says, a common understanding of what technology can achieve is still conspicuously absent.
  • Making ITS connections requires leadership
    January 23, 2020
    From making the commute more bearable to saving the planet, Jim Alfred of BlackBerry Certicom believes that ITS has the capacity to drive a range of transformational opportunities – but leadership is required, he warns
  • Roads revolution adds 900 miles of extra capacity
    August 27, 2014
    Road users in the UK will see around 900 extra lane miles of road capacity added to England’s strategic highway network by 2021, a third more than was provided in the previous decade. The boost is thanks to a huge US£39.7 billion investment, the biggest since the 1970s, which will see annual funding for enhancements to motorways and major A roads triple over the next six years. Investment includes more than US$15 billion on maintenance, US$10 billion of which will be spent on resurfacing 3,000 miles of t
  • After two decades of research, ITS is getting into its stride
    June 4, 2015
    Colin Sowman gets the global view on how ITS has shaped the way we travel today and what will shape the way we travel tomorrow. Over the past two decades the scope and spread of intelligent transport systems has grown and diversified to encompass all modes of travel while at the same time integrating and consolidating. Two decades ago the idea of detecting cyclists or pedestrians may have been considered impossible and why would you want to do that anyway? Today cyclists can account for a significant propor