A forward-looking perspective for data science in higher ed
Dr. Philip E. Bourne was itching to return to academia.
Phil had been working for three years as the associate director for data science at the National Institutes of Health (NIH), preceded by spending 20 years in the pharmacology department at the University of California, San Diego (UCSD). While at the NIH, he led the Big Data to Knowledge Program, which coordinated biomedical research and made it accessible to scientists and researchers around the world.
“But I really hankered after getting back to academia,” he says. “I missed the students. I missed the opportunities to innovate.”
An opportunity came to him in the form of the Data Science Institute (DSI). Phil had a connection with the University of Virginia through Dr. Jason Papin, professor of biomedical engineering, who was a student of his at UCSD.
Jason had mentioned the director position at the DSI, and Phil says he started to get very interested. Shortly thereafter, he came to Charlottesville for a few days. “I really liked the place. I really liked the people. I really thought this was something that was going somewhere,” he says.
Phil became the director of the DSI in May 2017, and he brings a wealth of experience to the role. Along with serving as a professor for two decades and leading the Big Data Knowledge Program at NIH, Phil worked as the chief data officer for a major $30 billion organization. Both at that company and at UCSD, he says that he learned about the vital importance of working across departments and industries.
“There’s clearly a lot of opportunity for that kind of collaboration in data science,” he says.
Phil is energized to build off of the incredible momentum of the DSI. “They’ve done a fabulous job,” he says. “That was part of the reasoning for coming here.”
And he’s ready to help take the DSI to the next level. Phil praises the strength of the Master of Science in Data Science (MSDS) program and is excited about expanding the DSI’s influence in the realm of research.
“I realized that DSI had a lot going on already with the state and with the private sector,” he says, “and we certainly want to continue to build on that.”
“The other major push, apart from the research, is the nationalization and internationalization of what we do,” he adds.
Another initiative that he is excited to bring to the DSI is a continued focus on openness. This concept of a commons, a virtual shared space to exchange information, is something that he thinks fits well with the spirit of the University. “It turns out to be a very Jeffersonian thing,” he says.
“Data scientists must have the ability to collaborate, to work on teams. That’s critical.”
A successful data scientist, in Phil’s mind, has the core training in statistics, machine learning and computer science, he says, “but that in itself does not make a data scientist.”
“It’s the ability to collaborate, to work on teams,” he says. “That’s critical.”
The interdisciplinary nature of the DSI, central to its mission when it was founded, continues to be a key virtue of the institute. Working together across a wide range of disciplines, Phil says, is what he regards as the core work of data science.
“To be successful, you need this ability to work with the various disciplines to actually maximize the use of tools within that particular type of data,” he says.
“That’s where I see the real excitement.”