Veronika Rockova is Assistant Professor in Econometrics and Statistics at the University of Chicago Booth School of Business. Her work brings together statistical methodology, theory and computation to develop high-performance tools for analyzing large datasets. Her research interests reside at the intersection of Bayesian and frequentist statistics, and focus on: data mining, variable selection, optimization, non-parametric methods, factor models, high-dimensional decision theory and inference. She has authored a variety of published works in top statistics journals. In her applied work, she has contributed to the development of risk stratification and prediction models for public reporting in healthcare analytics.
Co-Sponsored with Quantitative Social Science Colloquium (QSS), Department of Politics