معرفی
Matthias Neumann is an Assistant Professor at the Institute of Statistics, Graz University of Technology. He completed his PhD in 2020 at Ulm University under Prof. Volker Schmidt, earning the PhD prize of Ulm University. His research focuses on stochastic 3D modeling and statistical analysis of micro- and nanostructures for functional materials, including battery electrodes, fuel cells, and paper-based materials. He has received start-up funding from ProTrainU (2020-2022) and served as principal investigator in the POLiS Cluster of Excellence (2022-2023).
Research Interests: His work integrates mathematical morphology, machine learning, and spatial statistics to develop methods for microstructure quantification, estimation of geometrical descriptors (e.g., tortuosity, constrictivity), and data-driven models linking morphology to effective physical properties. He utilizes random fields, point processes, and copulas for virtual microstructure generation and parameter estimation.
Teaching: He lectures on Applied Statistics, Statistical Modeling, and Mathematical Statistics at Graz University of Technology, with prior teaching experience at Ulm University in Multivariate Stochastic Modeling, Point Processes, and Spatial Statistics.
Scientific Achievements:
- PhD prize of Ulm University (2020)
- ProTrainU start-up funding (2020-2022)
- POLiS Cluster of Excellence grant (2022-2023)
Publications: His 15 most recent articles (2023-2025) emphasize machine learning techniques for microstructure segmentation, stochastic 3D modeling of nanoporous materials, and data-driven quantification of transport-property relationships. Key topics include random forests, neural networks, and R-vine copulas applied to fuel cells, sodium-ion batteries, and polymer electrolytes.
