Gregor Kastner – Researcher of the Month
The title Researcher of the Month is awarded every month as a special recognition and appreciation of the research achievements of the distinguished person.
Gregor Kastner has been a researcher at WU’s Institute for Statistics and Mathematics since 2011. Many of you may have read about or heard of him in 2018, when he received a €2 million Young Independent Researcher Groups grant from the Austrian Science Fund (FWF) for an exciting research project, which he will presenting in his Researcher of the Month video.
A native of Upper Austria, Gregor Kastner holds degrees in technical mathematics and information management as well as teaching degrees in information technology, mathematics, and physical education. In 2014, Kastner earned a doctorate in technical mathematics from the JKU Linz, graduating under the auspices of the Federal President of the Republic of Austria (sub auspiciis praesidentis rei publicae). He has gained international experience during a one-year stay at ETH Zurich and as a visiting scholar at the University of Chicago Booth School of Business (USA) and the Jiangxi University of Finance and Economics (China).
Gregor Kaster’s research interests include Bayesian statistics and econometrics, computational statistics, and the mathematical modeling of uncertainty. His dissertation, entitled “Efficient Bayesian Inference for Univariate and High-Dimensional Stochastic Volatility Models,” won the Best Dissertation Award from the Austrian Statistical Association in 2015. Kastner has published successfully in internationally renowned journals, including the Journal of Econometrics, the Journal of Applied Econometrics, and the Journal of Computational and Graphical Statistics. He is a board member of the European Seminar on Bayesian Econometrics (ESOBE) and the Bayesian Young Statisticians Meeting (BAYSM), assistant editor of the Journal of Statistical Software, and associate editor of the ISBA Bulletin. Kastner has also been involved in organizing numerous international conferences and acts as a reviewer for leading journals in the fields of statistics and econometrics on a regular basis.
In his video, Gregor Kastner tells us why and how it will be possible to analyze high-dimensional data more quickly and more efficiently in the future.