International Conference On Preconditioning Techniques
For Scientific and industrial applications
27–29 MAY 2026
INTERNATIONAL CENTRE FOR MATHEMATICAL SCIENCES, EDINBURGH
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International Conference On Preconditioning Techniques
Welcome
Welcome
Preconditioning Techniques for Scientific and Industrial Applications is part of a series of international conferences focusing on preconditioning techniques for sparse and structured matrix computations. The key focus of the meeting is addressing timely challenges in mathematical computation with novel, rigorous, and creative iterative linear algebra approaches for scientific applications. Key current areas of active research include theoretical and practical questions related to randomized preconditioning, probabilistic interpretations, the design of efficient tensor-based methods, preconditioners tailored to modern HPC architectures, and physics-based preconditioners for solving extremely large-scale systems in modelling and simulations, to name a few. The meeting brings together researchers developing new methods and tools, along with scientists and engineers addressing complex issues of applying preconditioning techniques in large-scale and industrial settings.
Note for participants: Due to the exceptional number of excellent minisymposium proposals we have received, we have reached the capacity of the ICMS conference venue. We will open a call for contributed talks if additional capacity becomes available. If this happens, we will likely give some priority to talks submitted by early-career researchers. We are working on this, and will provide a further update when we have information to share.
This is a supporting WEBPAGE, for the main conference page LINKED BELOW:
This is a supporting WEBPAGE, for the main conference page LINKED BELOW:
PLENARY SPEAKERS
We are delighted that the following excellent plenary speakers have agreed to give talks at the meeting:
Mark Embree is the Hamlett Professor at Virginia Tech, and leads the program in Computational Modeling and Data Analytics. Mark's research interests include matrix theory, numerical analysis for non-self-adjoint operators, spectral theory, and reduced order models.
Alena Kopaničáková is an Associate Professor at the University of Toulouse and a member of the Parallel Algorithms and Optimization team in the IRIT Laboratory. Alena's research interests include scientific machine learning, multilevel and domain decomposition methods, scientific computing, and high performance computing.
Théo Mary is a Researcher at the Computer Science Laboratory (LIP 6) at Sorbonne Université. Théo's research interests include numerical linear algebra, high performance computing, low-rank methods, and mixed precision approaches.
Yuji Nakatsukasa is a Professor in the Mathematical Institute at the University of Oxford. Yuji's research interests include matrix analysis, randomized linear algebra, approximation theory, and eigenvalues and their applications.
Ben Southworth is a Scientist at the Los Alamos National Laboratory. Ben's research interests include multigrid approaches, parallel-in-time methods, the numerical solution of PDEs, as well as numerical linear algebra and scientific computing more broadly.
Jemima Tabeart is an Assistant Professor in the Computational Science group at TU Eindhoven. Jemima's research interests include data assimilation, applications to climate, model reduction, and numerical linear algebra.
Madeleine Udell is an Assistant Professor in the Department of Management Science and Engineering at Stanford University. Madeleine's research interests include optimization, machine, and the application of numerical linear algebra to such problems.
Preconditioning Techniques for Scientific and Industrial Applications
Edinburgh, 27–29 May 2026
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