Applied Mathematics (TIMA)

Applied mathematics is used to study advanced methods for modeling in technology as well as natural and social sciences. The Division of Applied Mathematics (TIMA) conducts research in computational mathematics, mathematical statistics and optimization.

Subject areas at the Division of Applied Mathematics (TIMA)

Computational Mathematics

Computational mathematics develops and analyses numerical methods and algorithms for the solution of problems in science and engineering.

Important topics are well-posedness of the governing partial differential equations and convergence of the numerical approximation. Accuracy, stability, efficiency, software aspects and computer implementation are important.

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Mathematical Statistics

Mathematical statistics is the science of randomness and probabilities.

The research within the subject is divided into probability theory and statistical inference, where statistical inference (how to draw conclusions from random data) is based on probability theory.




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Optimization

Optimization aims at finding the best solutions to difficult problems.

All large-scale and complex operations must be planned, especially where cost is a factor. In many cases, the problems are too difficult to solve for a human being. A common property for many of these problems is that they give large, difficult combinatorial models that require research to be resolved.

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Research areas at the Division of Applied Mathematics (TIMA)

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.

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.

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.

Decision support for railway crew planning

For our society to fully reap the benefits of sustainable train travel, careful resource planning is essential. Passengers need to be able to rely on that trains are on time and train operators need to make efficient use of their vehicles and crew.

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.

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.

Doctoral studies in Mathematics

Contacts at the Division of Applied Mathematics (TIMA)

Address

Visiting address

Department of Mathematics, B Building, entrance 21-25, Campus Valla

Postal address

Linköping University
Department of Mathematics
581 83 Linköping
Sweden

Seminars

Conference

New Publications

2025

Hendrik Ranocha, Andrew Ross Winters, Michael Schlottke-Lakemper, Philipp Oeffner, Jan Glaubitz, Gregor J. Gassner (2025) On the robustness of high-order upwind summation-by-parts methods for nonlinear conservation laws Journal of Computational Physics, Vol. 520, Article 113471 (Article in journal) Continue to DOI
Hendrik Ranocha, Andrew Ross Winters, Michael Schlottke-Lakemper, Philipp Öffner, Jan Glaubitz, Gregor J Gassner (2025) On the robustness of high-order upwind summation-by-parts methods for nonlinear conservation laws Journal of Computational Physics, Vol. 520, Article 113471 (Article in journal) Continue to DOI
David A. Kopriva, Andrew Ross Winters, Jan Nordström (2025) Energy Bounds for Discontinuous Galerkin Spectral Element Approximations of Well-Posed Overset Grid Problems for Hyperbolic Systems Journal of Computational Physics, Vol. 520, Article 113508 (Article in journal) Continue to DOI
Pauline Achieng, Fredrik Berntsson, Vladimir Kozlov (2025) Reconstructing of the radiation condition and solution for a variable coefficient Helmholtz equation in a semi-infinite strip from Cauchy data on an interior segment Journal of Mathematical Analysis and Applications, Vol. 541, Article 128684 (Article in journal) Continue to DOI

2024

Frida Dohlmar, Björn Morén, Michael Sandborg, Torbjörn Larsson, Åsa Carlsson Tedgren (2024) Dwell time shaping in inverse treatment planning for cervical brachytherapy Physics and Imaging in Radiation Oncology, Vol. 32, Article 100672 (Article in journal) Continue to DOI
Denise Uwamariya, Xiangfeng Yang (2024) On the Ratio of Extremal Eigenvalues of ß-Laguerre Ensembles THEORY OF PROBABILITY AND MATHEMATICAL STATISTICS (Article in journal) Continue to DOI
Oskar Ålund, Yukinao Akamatsu, Fredrik Laurén, Takahiro Miura, Jan Nordström, Alexander Rothkopf (2024) Correction: Corrigendum to "Trace preserving quantum dynamics using a novel reparametrization-neutral summation-by-parts difference operator" [J.Comput.Phys. 425 (2021) 109917] Journal of Computational Physics, Vol. 519, Article 113517 (Article in journal) Continue to DOI
Chuan He, Heng Huang, Zhaosong Lu (2024) A Newton-CG based barrier-augmented Lagrangian method for general nonconvex conic optimization Computational optimization and applications (Article in journal) Continue to DOI
Uledi Ngulo, Torbjörn Larsson, Nils-Hassan Quttineh (2024) A meta-heuristic extension of the Lagrangian heuristic framework Optimization Methods and Software (Article in journal) Continue to DOI
Jenny Enerbäck, Lukas Eveborn, Elina Rönnberg (2024) Pricing for the EVRPTW with Piecewise Linear Charging by a Bounding-Based Labeling Algorithm 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024), p. 3:1-3:18 (Conference paper) Continue to DOI