Applied Data Science @ Columbia

An Spring 2016 alum from our Applied Data Science course, Yuhan Sun (MA in Statistics, Columbia University), spent the past summer as a data scientist at UNICEF. She extended a Shiny app at UNICEF that provides a web-based application for generating child mortality estimates. These estimates are computed from empirical data using the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) methodology. According to Ms. Lucia Hug from UNICEF, “The UN IGME methodology applies a curve fitting method to derive trend estimates by using a Bayesian B-splines bias-reduction model to empirical of under-five and infant mortality rates. The method also extrapolates the trend estimates to a defined time point.”

Yuhan is happy to apply her skills on Shiny app development in our ADS course to meet the needs of this task. She said: “Shiny provides a feasible approach for non-cs people to build a web application. It is an effective and time efficient way to build an application which uses the existing R codes for the Bayesian B-spline bias-reduction model. It also enables users to use the UN IGME methodology without being familiar with running R codes. It allows to apply the model to new empirical data and to review the new estimates graphically. It also offers the possibility to visualize the results and to adjust parameters according to the users’ needs.”

Ms. Hug said: “Mortality rates among young children are a key output indicator for child health and well-being, and, more broadly, for social and economic development. It is a closely watched public health indicator because it reflects the access of children and communities to basic health interventions such as vaccination, to medical treatment of infectious diseases and to adequate nutrition.”

Yuhan is also working on some cool visualizations as part of her internship.