A new initiative at Columbia University Mailman School of Public Health aims to further elevate the School’s data science game in partnership with Columbia’s Data Science Institute (DSI), a university-wide effort to support the gathering and interpreting of data for social good. Post-doctoral fellows are now eligible for the program that provides training in areas such as machine learning — a branch of artificial intelligence — and network science, which could be used to shed light on intricate systems like the human microbiome.
“Data science gives us new tools to analyze complex challenges like climate change that present multiple, overlapping threats to human health,” says Dr. Gary Miller, Columbia Mailman’s vice dean for research strategy and innovation, who laid the groundwork for the DSI partnership. “Every area of public health can benefit from these approaches.”
Before students learn how to “train” a computer model, fellows are steeped in how to use “data for good,” in the words of Dr. Jeanette M. Wing, Avanessians Director of the Data Science Institute and professor of computer science. The responsible use of analytical tools is ever more important when the computer model affects our health, says Dr. Miller, a professor of environmental health sciences. “We need to take care to uncover hidden biases that could exacerbate disparities [in health outcomes] if the system was modeled incorrectly.”
Research collaborations through the DSI are already underway. Elsewhere at Columbia Mailman, there are other signs of accelerating interest in data science. A two-semester course in data science is offered through biostatistics, and other departments have started similar classes. Dr. Miller expects trainings in advanced quantitative methods will soon be available schoolwide.Friday Letter Submission, Publish on October 04