The impact of statistical analyses, uncertainty quantification, and data driven models on science and workforce in the 21st century

Prof. Dr. Frank Gronwald
Dr.-Ing. Michael G. Wahl


Engineering and natural sciences are ultimately based on laws of nature which traditionally are formulated in terms of mathematical equations. The exactness and accuracy of corresponding methods and models in the engineering and natural sciences are both fascinating and rewarding and have stimulated the creation of the technological world we nowadays live in. However, the emergence of thermodynamics in the 19th and quantum mechanics in the 20th century already indicated that our world also contains concepts of statistics, probability, and uncertainty. This is accompanied by technological developments which become extremely complex and difficult to handle. Therefore, data driven modeling, often being connected to notions such as “artificial intelligence” or “machine learning”, has attracted a lot of attention to deal with complex processes. It is the aim of this workshop to introduce to the topic and to discuss to which extent engineers and natural scientists need to adapt to the new developments in statistical analyses, uncertainty quantification, and data driven models in order to master future challenges both in academic research and within the actual workforce.