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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.
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.
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.
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 Computational Mathematics
The seminars in Computational Mathematics are organised by the Department of Mathematics.
Brachytherapy Treatment Planning
Our research on treatment planning for radiation therapy aims at obtaining better treatment outcomes and more efficient treatment planning at the clinic, by applying mathematical optimization on the multi-criteria treatment planning problem.
Scheduling of Avionic Systems
In an avionic system, communications and activities need to be scheduled to ensure the functionality of the aeroplane. Efficient methods for such scheduling are of importance for the development of future avionic systems.
Research collaboration in Mathematics with low income countries and regions
The Department of Mathematics contributes to the development of capacity for higher education and research in low income countries and regions through collaborative projects in Africa and Asia.
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.
Modern Multivariate Statistical Analysis
Nowadays there is a great need to analyse complex high-dimensional data. Modern theories must be developed through the knowledge of the classical methods of multivariate statistics.