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Optimization under Uncertainty
We aim to incorporate data-driven information to enhance existing optimization models and investigate how deterministic models can be protected against the influence of uncertain data.
Seminars in Optimization
The seminars are informal gatherings to exchange research ideas on optimization theory, algorithms, problems and applications. Organised by the Department of Mathematics.
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Seminars in Computational Mathematics
The seminars in Computational Mathematics are organised by the Department of Mathematics.
Applied Mathematics (TIMA)
Applied mathematics is used to study advanced methods for modeling in technology as well as natural and social sciences. The division conducts research in computational mathematics, mathematical statistics and optimization.
Mathematics and algorithms for intelligent decision-making
On the journey towards sustainability, our contribution is to develop mathematical models and solution methods for practically relevant but computationally challenging problems in scheduling and resource allocation.
WASP Academic Doctoral Student project
Pushing the limits for large-scale discrete optimisation: New mathematics and algorithms for methods used together with Dantzig-Wolfe decomposition.
Seminars in Mathematical Statistics
The seminars are organised by the Department of Mathematics and form part of the seminar series "Seminars in Statistics and Mathematical Statistics". The topic is probability theory, random processes, statistical theory, and applied statistics.
Numerical Solutions of Time-Dependent Partial Differential Equations
Well-posedness of the governing partial differential equations lead to effective and accurate numerical methods for the analysis of physical processes in science and engineering.
Computational Cardio-Oncology
Many pediatric cancer care survivors develop serious cardiovascular complications later in life. The emerging field of computational cardio-oncology leverages advanced data methods to better predict and prevent these complications.
Optimization of Snow Removal in Cities
Snow removal in a city is a major undertaking that requires route planning and efficient driving schedules. It is a difficult and complex optimization problem and research is needed to be able to get good solutions.