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 big datasets. Her research interests reside at the intersection of Bayesian and frequentist statistics, and focus on: data mining, variable selection, machine learning, non-parametric methods, factor models, dynamic models, high-dimensional decision theory and inference. She has authored a variety of published works in top statistics journals, including the Journal of American Statistical Association and the Annals of Statistics. In her applied work, she contributed to the improvement of risk stratification and prediction models for public reporting in healthcare analytics.
Prior to joining Booth, Rockova held a Postdoctoral Research Associate position at the Department of Statistics of the Wharton School at the University of Pennsylvania. Rockova holds a PhD in biostatistics from Erasmus University (The Netherlands), an MSc in biostatistics from Universiteit Hasselt (Belgium) and both an MSc in mathematical statistics and a BSc in general mathematics from Charles University (Czech Republic).
Beyond statistics, she is a keen piano and tennis player.
2020 - 2021 Course Schedule
|41201||Big Data||2021 (Spring)|