Huijing is a PhD student in the School of Industrial and Systems Engineering and a Graduate Research Assistant of Dr. Nicoleta Serban. Her research focuses on novel statistical methodology for data-intensive spatiotemporal systems. One motivating application is the study of U.S. demographics trends for socio-economics where data are commonly collected over space and time. Her key contribution consists of a series of approaches under the framework of Functional Spatial Methodology to overcome the challenges arising in modeling and inference of spatiotemporal correlations intrinsic to the data. Corporate and business units can use this information to help improve their business, identify locations for future business and predict regional economic growth.

Most recently, Huijing did an internship for Statistical Analysis and Forecasting Group at IBM where she investigated spatial-temporal models to forecast environment/business risk. Prior to joining the Tennenbaum Institute, Huijing worked for the Operations Research Group, Division of Strategic Planning at the Norfolk Southern Corporation. While at Norfolk Southern, she explored time-series/bayesian models to forecast future business.

Before joining Georgia Tech, Huijing received a B.S. degree in Chemistry from Tsinghua University (Beijing, China) and a M.S. degree from the School of Biochemistry and Biochemistry at Georgia Tech.