The **D**epartment **A**pplied **M**athematics** U**niversity of **T**wente contributes to mathematical development through connection to scientific research at UT institutes.

Key elements in our multidisciplinary collaborations are mathematical abstraction, structuring and generalisation, and the development of mathematical methods for analysis, modelling and simulation.

**DAMUT **finds a natural clustering in three methodologically oriented departments:

The Mathematics of Operations Research (MOR) research group consists of three research chairs.

We share a common graduate seminar in which students present their ongoing work on internships and final projects.

- Discrete Mathematics and Mathematical Programming (DMMP)our chair works in the mathematics and practice of Operations Research, in particular Combinatorial Optimization, Approximation & Online Algorithms, Mathematical Programming, Discrete Mathematics, Graph
- Stochastic Operations Research (SOR)our chair conducts mathematical education and research in the areas of stochastic processes and mathematics of operations research, to contribute to the development of mathematics in a multidisciplinary engineering environment.
- Statistics (STAT)our chair started in 2018 and will grow over the next years. The research focus is on the development of statistical methodology for new data applications and the theoretical analysis of machine learning methods.

Organized into two groups — Statistics (STAT) and Mathematics of Imaging & AI (MIA), our cluster shares a commitment to excellence in research and education, and our expertise emphasizes a balance among mathematical rigour, scientific value, and industrial relevance. In the era of AI and big data, we are making constant efforts to address fundamental challenges in data science such as uncertainty, bias, predictiveness, and interpretability, and we strive to train the next-generation data scientists and applied mathematicians who can make an impact in academia, industry, and society.

- Mathematics of Imaging & AI (MIA)our chair focuses on areas of dynamical systems, numerical analysis, and scientific computing, and, in particular, their relation to data science. The availability of extensive data sets offers new possibilities and challenges for research within MIA
- Statistics (STAT)our chair started in 2018 and will grow over the next years. The research focus is on the development of statistical methodology for new data applications and the theoretical analysis of machine learning methods.

The MCS research team will focus on the following topics in the area of dynamical systems, numerical analysis and scientific computing, systems and control, and in particular, their relation with data science. The availability of very large data sets offers new possibilities and challenges for research within MCS.

- Mathematics of Imaging & AI (MIA)our chair focuses on areas of dynamical systems, numerical analysis, and scientific computing, and, in particular, their relation to data science. The availability of extensive data sets offers new possibilities and challenges for research within MIA
- Mathematics of Computational Science (MACS)our chair will focus on the following topics in the area of numerical analysis and scientific computing
- Mathematics of Systems Theory (MAST)our chair will focus on the following topics in the area of systems and control
- Mathematics of Multiscale Modeling and Simulation (3MS)our chair will focus on the following topics in the area of dynamical systems, numerical analysis and scientific computing.