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Needed: More Women in Data Science

By Stanford Report

November 13, 2015

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Stanford University recently hosted the inaugural Women in Data Science conference, which brought together about 400 women to discuss data science and promote greater gender diversity in the field.

Attendees included students and professionals from the private sector, academia, and national laboratories. Speakers included Stanford professor Fei-Fei Li, who described her team's research into computer vision, which includes building a database of 15 million photos to train computer-vision systems.

"This is a dream for us, to organize a conference like this," says Margot Gerritsen, director of Stanford's Institute for Computational & Mathematical Engineering, which was the main sponsor of the event.

A major theme of the conference was the need to bring more women into the data science field. The demand for data scientists currently is extremely high, and "not tapping into 50 percent of our population of our talent would of course be a very silly thing to do," Gerritsen says.

"When there is a difficult challenge to address, and our world is full of difficult challenges, we need a diversity of thought, a diversity of approaches, a diversity of styles to get to the solutions--and that's why we need diverse teams," says Persis Drell, dean of Stanford's School of Engineering.

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