Data Analytics and Science

Our researchers are nationally recognized experts in data analytics. Their work includes investigating statistical problems arising in privacy and security analytics, the statistical analysis of literary style, and the statistical foundations of geometric and topological data analysis.

Data analytics research in the Department of Statistics addresses the growing need for statistical innovation in high-dimensional, dynamic, and unstructured data environments. Our work supports applications across geoscience, astronomy, neuroscience, urban systems, and healthcare, advancing both theoretical frameworks and computational tools that make sense of the data-rich world.

Our focus areas include high-dimensional modeling; spatio-temporal and longitudinal data analysis; statistical computing and data visualization; and exploratory analysis of aggregated data summaries. We also investigate topological and geometric data structures, point cloud analysis, data mining, and network modeling with applications in smart cities and digital systems. Additional expertise includes data compression, data integration, causal inference, and the interface of statistics with AI, machine learning, and computer science, empowering solutions in fields ranging from public health to cybersecurity.