Professor of Econometrics and Statistics, and James S. Kemper Foundation Faculty Scholar
Veronika Rockova is Professor of Econometrics and Statistics and the James S. Kemper Faculty Scholar at the Booth School of Business at the University of Chicago. She joined Booth after completing her postdoctoral training in statistics at the Wharton School of the University of Pennsylvania. She teaches a course on Big Data at Booth. Her research interests lie at the intersection of statistics and machine learning, with a primary focus on creating innovative decision-centric tools for extracting insights from extensive datasets. She specializes in Bayesian computation, high-dimensional decision theory, and hierarchical modeling. Her applied areas of interest include healthcare analytics and computational medicine. Her research was acknowledged with the National Science Foundation CAREER Award in 2020, the COPSS Emerging Leader Award in 2023 and the COPSS President's Award in 2024. She currently serves as an associate editor for the Annals of Statistics, Journal of the American Statistical Association, and the Journal of the Royal Statistical Society.
Beyond her academic pursuits, Veronika is an avid pianist, tennis enthusiast, and golf neophyte.
| Number | Course Title | Quarter |
|---|---|---|
| 41201 | Big Data | 2024 (Spring) |
Machine learning is being tasked with an increasing number of important decisions. But the answers it generates involve a degree of uncertainty.
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The most influential rating system rests on some faulty calculations, affecting millions of people and billions of dollars.
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The US federal government’s hospital scoring can be woefully inaccurate, research suggests, giving many small hospitals undue boosts.
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