The Chair of Applied Mathematics conducts research in stochastics, operations research, and applied/digital mathematics.

In stochastics, two new projects funded by the Austrian Science Foundation study how random processes influence chemical and biological systems. Further work combines deep learning with stochastic methods to develop strategies for energy market trading, including anticipating random crashes.

In operations research, the focus lies on optimization algorithms for the digitalization of industrial logistics. In collaboration with KFU Graz, Dr. Stanek develops algorithms for complex covering problems and a new, faster matching algorithm for job distribution, resource allocation, and partner matching.

Due to the increasing importance of digitalization, applied mathematics plays a growing role. Algorithmic and quantitative methods shape modern technology—for example, the Fast Fourier Transform underpins speech recognition, streaming, and real-time communication.

Optimization, numerical methods, and operations research support efficient resource use, which is essential for climate neutrality. Understanding uncertainty and randomness is central to data science, machine learning, and data processing. A new course in Stochastics will be offered next year as part of the Industrial Data Science curriculum, and a lecture on programming in Python is also available.