Twenty-eight undergraduate students from across the United States and the globe arrived at the Yale School of Public Health in mid-June with stories to tell about themselves. They had some foundations in data science, they said, but wanted to improve their knowledge and learn more. They were particularly curious about how their coding skills can improve human health. Some wanted to be physicians, many wanted to be statisticians or data scientists. Most wanted to explore options for their future.
While they came away from Big Data Summer Immersion at Yale (BDSY) with more confidence in their data science skills, they learned something more – how to think and talk about science and the science of data.
For Abhroneel Ghosh, who came all the way from the Indian Statistical Institute, that means having a new understanding about how statistics can be used to solve health challenges and make a difference in the world. Anthony Zhao from Duke University, who is planning to apply to medical school, became interested in how patient data can be collected and applied to public health research.
Isabelle Summe from the University of Chicago, who wants to work in cancer research, saw public health more clearly. “Public health has more doors open to making real change in peoples' lives,” she said. So did Tony Bolea, a Yale College student who was introduced to the concept of data equity. “I didn’t realize that data inequality can lead to inequitable outcomes,” he said.
"The students learned to see the world of science more broadly, and to tell stories about it,” said Dr. Bhramar Mukherjee, PhD, senior associate dean of public health, data science, and data equity. “Through hands-on training, mentorship, and collaboration, these future leaders explored how big data can contribute to human flourishing,” said Mukherjee, PhD, who launched BDSY at YSPH this summer after leading a similar program at the University of Michigan for 10 years. She is also the Anna M.R. Lauder Professor of Biostatistics, professor of epidemiology (chronic diseases) and of statistics and data science.