Duke's Data Network

In a place where engineers can (and do) simply cross the street or even the hallway to connect with Medical Center clinicians, statisticians, or energy experts, it’s perhaps not surprising that Duke’s data-science research is literally all over the map—with teams coming together from across disciplines to apply analytics to knotty problems in healthcare, environmental sustainability, materials discovery and more.

“In the information age, data science is key to advancing progress on a number of globally important fronts,” says Ravi Bellamkonda, dean of engineering. “We recognize that strength in data science is a strategic advantage in many disciplines, which is why we’re expanding our already outstanding corps of faculty both in engineering and across the university.”

“Duke faculty are known for working across department and school lines, but over the past five years we’ve created a number of mechanisms specifically to connect our data scientists with faculty who can tap into their expertise to solve problems in other fields,” adds Lawrence Carin, professor in ECE and vice provost for research at Duke.

Duke Engineering professors have played key roles in these efforts, including the Information Initiative at Duke—a hub of research and teaching where “superb data science can be thoughtfully focused to transform every discipline in the university,” as director Robert Calderbank puts it—and the Duke Quantitative Initiative, launched to hire up to 10 new faculty in the broad area of quantitative sciences with the express goal of strengthening cross-university connections, particularly with Duke Health. Duke MEDx, a new joint initiative of Duke’s engineering and medical schools, is also spurring innovation through seed funding for collaborative data-driven research.

“Duke is in an unusually strong position to make advances in the data science of health,” Carin says, pointing to collaborations with the university’s top-10 medical school and nationally recognized health system on projects ranging from early disease diagnosis to the social science of population health management.

Engineering students are intimately involved in the work, too—for example, a new Mobile Health Application Prototyping Group launched this semester by the Duke Institute for Health Innovation is pairing physicians with undergraduates to develop digital apps for real-world mobile health care and clinical research projects.

Broader afield, Duke engineers are diving into data-based explorations of the microbiome with biologists and statisticians, examining solar capacity with colleagues from Duke’s Energy Initiative, and sifting data to discover new materials, among others. Here are just a few examples of how our faculty are bringing big data expertise to bear upon big questions:

• Predicting Patient Outcomes
• Data-based Diagnosis
• Teaming the Microbiome
• An App for Autism Screening
• Interpretable Machine Learning
• Demystifying Deep Neural Networks
• Analyzing Art
• Materials Discovery
• A Global Approach to Nanoinformatics
• Understanding Complex Infrastructure Systems
• Data-Based Models Inform Environmental Policy