An Argentine mathematician won the academic prize for Statistics, equivalent to the Nobel

The Argentine scientist and professor at the Torcuato Di Tella University (UTDT) Andrea Rotnitzky he won Rousseeuw Prize for his work in statistics, an award equivalent to a Nobel Prize in statisticsfor their work, together with a group of colleagues, in research on causal inference and its use in medicine and public health.

As reported by the King Baudouin Foundation, based in Brussels (Belgium), Rotnitzky and four other scientists specialized in the field of statistics, “the team is recognized for pioneering research on causal inference with applications in medicine and public health. Causal inference is the process of determining causes and effects.

The winners, in addition to Andrea Rotnitzky, were James Robins, Miguel Hernan, Thomas Richardson Y Eric TchetgenTchetgen. The award will take place on October 12 in a ceremony at the University of Leuven, in Belgium.

Andrea Rotnitzky won the Rousseeuw Prize for her work in statistics, an award for that discipline equivalent to a Nobel Prize for her research on causal inference applied to public health and medicine

“This biennial prize, worth 1 million, was established by Peter Rousseeuw, professor of statistics at Leuven. Its objective is to reward excellence in statistical research that has a significant impact on everyday life.”, communicated the Foundation.

“The laureates’ work has provided new insights and statistical methods to address core epidemiological questions. For example,What is the effect of long-term medical treatment? And, if beneficial, what treatment strategies are optimal? The work of the laureates, for example, has resulted in guidelines on when best to start antiretroviral therapy in people with HIV”, they exemplified.}

“The work of the laureates has had a great influence on statistical practice in medicine and public health. It has also spread to other fields, such as economics and psychology. In several important cases, he has shown that disparities between the conclusions drawn from experimental and non-experimental studies are due to the use of older statistical methods that were not adequate. Examples that have had both scientific and social impact include studies of postmenopausal hormone therapy in coronary heart disease; statin treatment in cancer; the benefits of anti-inflammatory therapy for patients with Covid-19″.

According to her profile at UTDT, Andrea Rotnitzky is Full Professor in the Department of Economics at UTDT, adjunct professor at Harvard TH Chan School of Public Health and principal investigator at Conicet. He has scientific articles published in Biometrika, Journal of the American Statistical Association, Biometrics and Journal of the Royal Statistical Science, among others. She was associate editor of Biometrics, Annals of Statistics, Statistical Science, and the Journal of Causal Inference. She is currently an associate editor of the Journal of the American Statistical Association.

Rotnitzky’s work “focuses on the development of analytical tools to estimate, from observational data or imperfect experimental data, causal effects of treatments. This work falls into the general area of ​​causal inference and analysis of missing and censored data”, summarized the UTDT.

Rotnitzky’s research includes modern and flexible machine learning methods for causal inference; efficient estimation of the causal effect in causal graphical models; estimation, from longitudinal databases of electronic medical records, of the causal effects of treatment strategies dependent on covariates; methods for evaluating diagnostic markers from studies suffering from verification bias.

Rotnitzky is a Plenary Professor in the Department of Economics at UTDT, an adjunct professor at the Harvard TH Chan School of Public Health, and a principal investigator at Conicet.

Also other methods such as the correction of the lack of informative response in longitudinal studies; to analyze the survival time in studies with opposing informative causes of censorship and for the analysis of clinical trials with non-compliance.

Rotnitzky received her bachelor’s degree in mathematics from the University of Buenos Aires in 1982 and continued her training in statistics at the University of California. Since 2005 she has been an adjunct professor of biostatistics at Harvard University and a professor in the Department of Economics at UTDT. In 2012 she was named Conicet principal investigator.

The news, which was known this Monday, was celebrated by some of his peers at the Torcuato Di Tella University. The rector of that center of higher studies John Joseph Cruces mentioned that “it is a great pride for the Univ. Torcuato Di Tella that Andrea Rotnitzky, Plenary Professor of the Dept. of Economy, has received, together with colleagues from different parts of the world, this very important prize in Statistics. Congratulations!”.

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