Megan Price | Data Science and the Fight for Human Rights

11/20/18 • 46 min

Data scientists are involved in a wide array of domains, everything from healthcare to cybersecurity to cosmology. Megan Price and her colleagues at the Human Rights Data Analysis Group (HRDAG), however, are using data science to help bring human rights abusers to justice.

The nonpartisan group played a key role in the case of Edgar Fernando García, a 26-year-old engineering student and labor activist who disappeared during Guatemala’s brutal civil war. Price, the executive director of HRDAG, says the investigation took years, but their work led to the conviction of two officers who kidnapped Garcia and the former police chief who bore command responsibility for the crime. “It was one of the most satisfying projects that I’ve worked on,” she says. Price discussed the case in more detail as well as other cases she’s worked on over the years and the role data science played in an interview recorded for the Women in Data Science podcast recorded at Stanford University.

For a recent project in Syria, Price’s group used statistical modeling and found information previously unobserved by local groups tracking the damage caused by the war. Similarly, in Mexico, she expects HRDAG to gain a better understanding of in-country violence by building a machine learning model to predict counties with a higher probability of undiscovered graves.

Price hopes that in the future human rights and advocacy organizations will have their own in-house data scientists to further combat social injustices around the world, and she believes that data science will continue to play an important role in the field. She advises young people entering the field of data science and social change to learn a programming language, pick an editor and find mentors and cheerleaders to help them along the way.

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Eileen Martin + Nilah Monnier Ioannidis | Data in Seismology and Genomics Research

Fiber optic cables that convey data at high speeds across the globe area is a well-known feature of modern technology. Now, university data scientists have found a unique use for them: monitoring earthquakes.Distributed across Stanford’s telecom infrastructure, the cables have become a seismic array that has already collected data on over 1,000 Bay Area earthquakes, says Eileen Martin, a recent alumnus of Stanford’s Institute for Computational and Mathematical Engineering, now Assistant Professor at Virginia Tech, whose research is focused on seismology. Martin and Nilah Monnier Ioannidis, a postdoctoral scholar concentrating on data science and genomics at Stanford, sat down to discuss the pivotal role of data in their research for the Women in Data Science podcast.

Despite coming from different fields, both researchers tout the importance of data in academic research. Genomic sequencing requires vast amounts of data, but privacy concerns mandate important restrictions, Ioannidis says. Consequently, she is collaborating with outside institutions that have already amassed large stores of genomic data to understand its role in the field of genomics. Kaiser Permanente is among those collaborations; the company has already done a large-scale genomics study for Northern California. Martin says that being open with other researchers and sharing ideas is a real plus in the field. Ioannidis echoes these sentiments. While Martin acknowledges the risk that another researcher will use the shared information, she adds, “We’re all busy trying to do our own experiments.” Their advice for students looking to pursue a career in data science within academia: look for new experimental techniques because there will always be an interesting math or computing problem to solve.

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Sonu Durgia | Optimizing the Online Shopping Experience

Consumers know Walmart as a retailing giant that has changed the face of retail in communities across America. But with a data store containing billions of queries and items, it’s also a laboratory for the company’s data scientists and IT professionals who mine and manage it. “We have data scientists embedded in every single team within the company,” says Sonu Durgia, group product manager for search and discovery at Walmart Labs. “Every function at Walmart, from the quality of groceries to the supply chain, has data science embedded in it,” she noted during an interview recorded for the Women in Data Science podcast at Stanford University.

Because Walmart’s product catalog is immense, holding the attention of consumers and helping them find what they want to buy is a challenge. “We do not have your attention for the next several hours. We have to show you the right things very, very quickly. So it's a ranking and relevance problem right there, even though it's not coming from a query,” Durgia says.
Explaining the insights of data scientists to the business and retail sides of Walmart, people who are not always conversant with technical issues is an important part of her job, she says. Her varied career path has provided her with the expertise to interact successfully with Walmart’s line of business executives. “My engineering degree gives me those tools to really understand the (algorithms) and work with these engineers and very savvy data scientists. My finance background gives me that bird's eye view, understanding what the key things are here,” she says.

Because data science is still a male-dominated discipline, finding a role model can be difficult for women in the field. But technology, says Durgia, has enabled new ways for women to find role models. “Back in the day, you would just look at your peer group to find inspiration or even to solve some problems, ask about a concept you didn't get in class. But now YouTube is your teacher. Everything is available,” she says.