Merging Computer Science and Business

What does computer science have to do with business school? A lot, says Louiqa Raschid, professor of information systems at the University of Maryland’s Robert H. Smith School of Business.

“If you go back a long time, business schools tended to be where certain technology areas started,” she says. “If you look at origins of data management, that was also very mathematically driven from optimization.”

That’s why Raschid, who also holds appointments at the UMD Institute for Advanced Computer Studies and the Department of Computer Science, has kept one foot inside Maryland Smith ever since she earned her doctorate in electrical engineering from the University of Florida.

Growing up in Sri Lanka, she says, she found “a lot of interesting technology, but not necessarily information technology.” During graduate school, she became interested in working with information, and enjoyed computer science and uncovering how problems were solved, computationally. At the time, data management and artificial intelligence (AI) were separate systems, and she was interested to see what would happen if you combined them. That became the focus of her thesis.

Throughout her career, Raschid has continued to examine this relationship and the challenges of data management, data integration and performance across a wide range of fields, including business information systems and life science data management. Her expertise is equally wide-ranging, from optimization and large-scale simulation to modeling and semantics and logic-based reasoning.

Though Raschid’s contributions are numerous, she’s most proud of two in particular.

One was her work with biomedical datasets, where she collaborated with a biology specialist about the way a particular plant’s cells were transporting chemicals. “I remember asking her questions and she kept referring me to her research papers,” she laughs. “She had spent 30-plus years becoming an expert, and I had spent a few months and didn’t have the knowledge she had, but the fact that she was referring me to her papers meant she was treating me like an equivalent domain expert – and it was because my technology was giving me insight into her data.”

The other project examined whether the financial crisis of 2008 could have been averted, had regulators been provided different data and tools. “It’s not that easy,” she prefaces. She gathered prospectuses – which are public – and built models based on the data extracted. She found patterns emerging within the products. “Investors were looking at specific securities and prospectuses, but not looking at all of them nor monitoring the change over time,” she says. People recognized there were problems, she says, but they might have been able to pin down the companies that were involved if they had the proper tools at hand.

Raschid is also well-versed when it comes to disaster information management, having coordinated efforts to share disaster data using open ontologies, standards and protocols. She is the founding chair of the Sahana FOSS project for disaster information management, which was initiated after the 2003 tsunami and was deployed for the 2010 Haiti earthquake, Hurricane Sandy, and refugee registration in Germany in 2015.

Currently, she is working on a project supported by the National Science Foundation (NSF) related to open knowledge networks and business.

At Maryland, she teaches a database class and another in web application development. Even though technology changes rapidly, data management itself hasn’t changed much through the years, she says. “It’s very fundamental, like arithmetic. Even if you look at the web, or Facebook, or so on. We describe them in this different context, but the fundamentals remain the same.”

What have changed, Raschid points out, are business school curriculums. At one point, they started moving away from mathematics and statistics and more toward theoretical applications, such as economics. But now, because of an interest in AI and certain technologies, schools are turning back to straight-up math. “It’s very cyclical.”

–By Rin-rin Yu

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