Data will become a more important part of problem-solving as America’s urban centers continue to gain a greater share of the U.S. population, and students at Virginia Tech are part of a forward-looking research program that uses data in an interdisciplinary approach to address areas of concern to urban planners, government policymakers and local communities.
Virginia Tech created UrbComp, a 12-credit urban computing graduate certificate program, to train students to become interdisciplinary and ethical data scientists who will help society cope with problems that will become more complex in areas from transportation to epidemiology as more American cities grow into vast metropolitan areas over the next 20 years.
Now in its fourth year, UrbComp has nine National Science Foundation fellows working with one academic adviser in each of two fields – a “horizontal” discipline such as computer science, math or statistics and a “vertical” discipline such as epidemiology, transportation or urban planning.
The purpose is to get them thinking and collaborating across disciplines and departments to broaden their knowledge bases and thinking as they partner with government and industry to solve problems using data.
At a presentation Thursday titled “Behind the Algorithm: Using Data to Solve Urban Challenges,” program director Dr. Naren Ramakrishnan described several examples of UrbComp projects, such as one that helped the Washington Metropolitan Area Transit Authority better allocate resources and improve service by using data to predict on-time performance of its trains through real-time forecasting.
Another UrbComp project involved mapping Tweets and mining social media data in other ways to understand WMATA service disruptions in real time, while another analyzed how to prevent implicit prejudices within complex crime data and bias in how the data is applied.
“It needs to be a really data-driven approach,” said Ramakrishnan, the Thomas L. Phillips Professor of Engineering. “What has really been useful is a lot of organizations either do not have data or the capacity to work it. So, a collaborator right here in the region, and the partnership, is helpful. Students and partners win. Students come up with real solutions to their problems.”
