Data+ 2017 has accepted 70 students to research and work in interdisciplinary project teams over the summer, starting May 22. The program will run 10 weeks, during which project teams will work on data provided by their clients and learn to marshal, analyze, and visualize that data based on the client’s goals for each project. “This year it was a very large applicant pool, and it was hard to make all of these decisions,” Co-Director Paul Bendich says.
Our 2017 Data+ students identify as 47.2 percent female and 52.8 percent male. 25 percent are from the class of 2020, 39 percent class of 2019, 13 percent class of 2018, 7 percent class of 2017, and 16 percent masters students of various kinds. In keeping with the interdisciplinary mission of the Data+ program, Data+ undergraduate majors this year come from: Biology, Biomedical Engineering, Chemistry, Computer Science, Cultural Anthropology, Economics, Electrical and Computer Engineering, English, Environmental Science, Evolutionary Anthropology, Finance, Global Health, International Comparative Studies, Mathematics, Mechanical Engineering, Neuroscience, Physics, Pre-Med, Psychology, Public Policy, Sociology, and Statistics. Now in its fourth year, Data+ continues to become more competitive.
Each of the 25 project teams will give two talks over the course of the program about their data, challenges and successes, and what they have learned. Talks will be on Mondays, Wednesdays, and Friday mornings in Gross Hall 107.
To learn more about the progress of Data+ 2017 projects this summer, keep an eye on our Events Page or the Duke Calendar for announcements as they start crunching data on May 22.
Data Viz for Long-term Ecological Research and Curricula: A team of students led by Biology Professor Emily Bernhardt will develop interactive R Shiny data visualization apps that will allow students and researchers to understand sixty years of ecological data collected at Hubbard Brook Experimental Forest.
Visualizing Real Time Data from Mobile Health Technologies: A team of students led by School of Nursing professor and health informatician Ryan Shaw will create visualizations of time series mobile health data in diabetes patients.
Digital Rejuvenation of Medieval Paintings: A team of students led by Mathematics professor Ingrid Daubechies will explore the feasibility of building an app that museum visitors could use to virtually rejuvenate paintings in museums. The app would require photographs taken by the user in the museum, as well as high resolution images provided by the museum website.