Marco Oesting has accepted the appointment as W3 Professor at the University of Stuttgart. This follows the successful evaluation of his tenure-track professorship in Computational Statistics, which was established as part of the federal and state programme “1,000 Tenure-Track Professorships” . The proposal for the professorship was jointly developed by the Stuttgart Center for Simulation Science (SimTech) and the Faculty of Mathematics and Physics. With the permanent establishment of the professorship, SimTech and the faculty gain long-term expertise at the interface of statistics, simulation, and data-driven modelling.
Marco Oesting has been at the University of Stuttgart since August 2020. His professorship is located at the Institute of Stochastics and Applications within Faculty 8 and at the Stuttgart Center for Simulation Science. Together with his research group, he develops and analyses statistical methods for complex, heterogeneous, and large-scale data.
His research focuses on extreme value theory and statistics, spatial statistics, and the simulation of stochastic processes and random fields. These methods are particularly relevant when rare or spatially complex events are investigated — for example heavy rainfall, droughts, or other questions in climate and environmental sciences. At the same time, Computational Statistics makes important contributions to the analysis, uncertainty quantification, and validation of data-driven simulation models.
Since joining the University of Stuttgart, Marco Oesting has significantly expanded his research profile and further strengthened its international visibility. In addition to publishing in renowned specialist journals, he is strongly engaged in academic networking and international collaboration, including through the organisation of conferences, workshops, and a summer school. As a junior professor at the Stuttgart Center for Simulation Science and in the Cluster of Excellence SimTech, his work has been interdisciplinary from the outset.
Marco Oesting is also highly committed to teaching, supervision, and the promotion of early-career researchers. His courses are consistently evaluated very positively by students. In 2023 — after only two years as a junior professor — he received the Teaching Award of the Faculty of Mathematics and Physics. The award is presented annually by the students of the faculty based on course evaluations. In addition, Oesting has supervised an above-average number of bachelor’s and master’s theses and supports early-career researchers in ongoing and completed doctoral projects.
Beyond research and teaching, Marco Oesting has also helped shape SimTech’s science communication activities. He regularly contributes to public events, exhibitions, and outreach formats, where he engages directly with visitors, school classes, and other audiences. In doing so, he helps make statistical methods and their importance for simulation and data-based research visible and accessible.
“The acceptance of the W3 professorship is a very positive development for SimTech and the Faculty of Mathematics and Physics. Marco Oesting combines fundamental mathematical-statistical research with key questions in data-integrated simulation science and is also highly committed to research, teaching, and science communication,” says Holger Steeb, Director of the Stuttgart Center for Simulation Science.
In the coming years, Marco Oesting plans to further expand his research at the interface of statistics, simulation, and machine learning. His focus will be on flexible models for high-dimensional data, more comprehensive uncertainty quantification, and the further development of hybrid methods that combine classical statistical approaches with machine learning.
“I am very pleased to continue my work at the University of Stuttgart and at SimTech in the long term,” says Marco Oesting. “Especially in SimTech’s interdisciplinary environment, I see great potential for joint projects. I want to advance research, for example through flexible models for high-dimensional data, more comprehensive uncertainty quantification, and hybrid methods that combine classical statistics with machine learning.”
With the W3 professorship, the University of Stuttgart strengthens its profile in a research field that is essential for processing and interpreting growing volumes of data, as well as for the further development of reliable simulation models. At the same time, the professorship creates long-term perspectives for collaboration across disciplinary boundaries — from mathematics and computer science to engineering and applications in environmental and climate research.
