Stefan Güttel

Professor of Applied Mathematics
The University of Manchester
Alan Turing Building
Manchester, M13 9PL, UK

☎ +44 161 275 5849
✉ stefan.guettel@manchester.ac.uk

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Intro

My main research interests are in computational mathematics, including numerical algorithms for large-scale problems arising with differential equations and in data science.

Brief academic CV

Current roles

Current projects

I enjoy working with industry partners. Companies I have engaged with through Knowledge Transfer Partnerships, PhD/MSc projects, or one-to-one consultancy include Arup, AspenTech, Autotrader, Intel, N Brown Group, Process Integration Ltd, and Schlumberger-Doll Research. (And here's my maths ancestry.)
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Publications

Google Scholar  |   complete BIB file

Articles in peer-reviewed journals

  1. S. Güttel and J. W. Pearson. A spectral-in-time Newton--Krylov method for nonlinear PDE-constrained optimization. IMA Journal of Numerical Analysis (online first), 2021. [Preprint]  [BibTeX]
  2. S. Güttel and M. Schweitzer. A comparison of limited-memory Krylov methods for Stieltjes functions of Hermitian matrices. SIAM Journal on Matrix Analysis and Applications, 42 (1): 83-107, 2021. [Preprint]  [BibTeX]
  3. I. V. Gosea and S. Güttel. Algorithms for the rational approximation of matrix-valued functions. SIAM Journal on Scientific Computing, 43 (5): A3033-A3054, 2021. [Preprint]  [BibTeX]
  4. E. Poupard, W. P. Heath and S. Güttel. A Hamiltonian decomposition for fast interior-point solvers in model predictive control. Automatica, 131: 109833, 2021. [Preprint]  [BibTeX]
  5. S. Güttel, D. Kressner and K. Lund. Limited-memory polynomial methods for large-scale matrix functions. GAMM-Mitteilungen, 43 (4): e202000019, 2020. [Preprint]  [BibTeX]
  6. S. Elsworth and S. Güttel. ABBA: adaptive Brownian bridge-based symbolic aggregation of time series. Data Mining and Knowledge Discovery, 34: 1175-1200, 2020. [Preprint]  [BibTeX]
  7. S. Elsworth and S. Güttel. The block rational Arnoldi method. SIAM Journal on Matrix Analysis and Applications, 41 (2): 365-388, 2020. [Preprint]  [BibTeX]
  8. C. Qiu, S. Güttel, X. Ren, C. Yin, Y. Liu, Bo Zhang and G. Egbert. A block rational Krylov method for three-dimensional time-domain marine controlled-source electromagnetic modeling. Geophysical Journal International, 218: 100-114, 2019. [Preprint]  [BibTeX]
  9. S. Elsworth and S. Güttel. Conversions between barycentric, RKFUN, and Newton representations of rational interpolants. Linear Algebra and its Applications, 576: 246-257, 2019. [Preprint]  [BibTeX]
  10. S. Güttel and J. W. Pearson. A rational deferred correction approach to parabolic optimal control problems. IMA Journal of Numerical Analysis, 38 (4): 1861-1892, 2018. [Preprint]  [BibTeX]
  11. T. Kinyanjui, Jo Middleton, S. Güttel, J. Cassell and J. Ross. Scabies in residential care homes: Modelling, inference and interventions for well-connected population sub-units. PLOS Computational Biology, 14 (3): 1-24, 2018. [Preprint]  [BibTeX]
  12. M. Berljafa and S. Güttel. The RKFIT algorithm for nonlinear rational approximation. SIAM Journal on Scientific Computing, 39 (5): A2049-A2071, 2017. [Preprint]  [BibTeX]
  13. M. Berljafa and S. Güttel. Parallelization of the rational Arnoldi algorithm. SIAM Journal on Scientific Computing, 39 (5): S197-S221, 2017. [Preprint]  [BibTeX]
  14. S. Güttel and F. Tisseur. The nonlinear eigenvalue problem. Acta Numerica, 26: 1-94, 2017. [Preprint]  [BibTeX]
  15. V. Druskin, S. Güttel and L. Knizhnerman. Near-optimal perfectly matched layers for indefinite Helmholtz problems. SIAM Review, 58 (1): 90-116, 2016. [Preprint]  [BibTeX]
  16. S. Güttel and Y. Nakatsukasa. Scaled and squared subdiagonal Padé approximation for the matrix exponential. SIAM Journal on Matrix Analysis and Applications, 37 (1): 145-170, 2016. [Preprint]  [BibTeX]
  17. M. Berljafa and S. Güttel. Generalized rational Krylov decompositions with an application to rational approximation. SIAM Journal on Matrix Analysis and Applications, 36 (2): 894-916, 2015. [Preprint]  [BibTeX]
  18. S. Güttel, E. Polizzi, P. Tang and G. Viaud. Zolotarev quadrature rules and load balancing for the FEAST eigensolver. SIAM Journal on Scientific Computing, 37 (4): A2100-A2122, 2015. [Preprint]  [BibTeX]
  19. R-U. Börner, S. Güttel and O. G. Ernst. Three-dimensional transient electromagnetic modeling using rational Krylov methods. Geophysical Journal International, 202 (3): 2025-2043, 2015. [Preprint]  [BibTeX]
  20. A. Frommer, S. Güttel and M. Schweitzer. Convergence of restarted Krylov subspace methods for Stieltjes functions of matrices. SIAM Journal on Matrix Analysis and Applications, 35 (4): 1602-1624, 2014. [Preprint]  [BibTeX]
  21. S. Güttel, R. Van Beeumen, K. Meerbergen and W. Michiels. NLEIGS: A class of fully rational Krylov methods for nonlinear eigenvalue problems. SIAM Journal on Scientific Computing, 36 (6): A2842-A2864, 2014. [Preprint]  [BibTeX]
  22. S. Güttel and G. Klein. Efficient high-order rational integration and deferred correction with equispaced data. Electronic Transactions on Numerical Analysis, 41: 443-464, 2014. [Preprint]  [BibTeX]
  23. A. Frommer, S. Güttel and M. Schweitzer. Efficient and stable Arnoldi restarts for matrix functions based on quadrature. SIAM Journal on Matrix Analysis and Applications, 35 (2): 661-683, 2014. [Preprint]  [BibTeX]
  24. E. Jarlebring and S. Güttel. A spatially adaptive iterative method for a class of nonlinear operator eigenproblems. Electronic Transactions on Numerical Analysis, 41: 21-41, 2014. [Preprint]  [BibTeX]
  25. S. Güttel and J. Pestana. Some observations on weighted GMRES. Numerical Algorithms, 67 (4): 733-752, 2014. [Preprint]  [BibTeX]
  26. S. Güttel. Rational Krylov approximation of matrix functions: Numerical methods and optimal pole selection. GAMM-Mitteilungen, 36 (1): 8-31, 2013. [Preprint]  [BibTeX]
  27. S. Güttel and L. Knizhnerman. A black-box rational Arnoldi variant for Cauchy--Stieltjes matrix functions. BIT Numerical Mathematics, 53 (3): 595-616, 2013. [Preprint]  [BibTeX]
  28. P. Gonnet, S. Güttel and L. N. Trefethen. Robust Padé approximation via SVD. SIAM Review, 55 (1): 101-117, 2013. [Preprint]  [BibTeX]
  29. M. J. Gander and S. Güttel. PARAEXP: A parallel integrator for linear initial-value problems. SIAM Journal on Scientific Computing, 35 (2): C123-C142, 2013. [Preprint]  [BibTeX]
  30. S. Güttel and G. Klein. Convergence of linear barycentric rational interpolation for analytic functions. SIAM Journal on Numerical Analysis, 50 (5): 2560-2580, 2012. [Preprint]  [BibTeX]
  31. B. Beckermann and S. Güttel. Superlinear convergence of the rational Arnoldi method for the approximation of matrix functions. Numerische Mathematik, 121 (2): 205-236, 2012. [Preprint]  [BibTeX]
  32. M. Eiermann, O. G. Ernst and S. Güttel. Deflated restarting for matrix functions. SIAM Journal on Matrix Analysis and Applications, 32 (2): 621-641, 2011. [Preprint]  [BibTeX]
  33. B. Beckermann, S. Güttel and R. Vandebril. On the convergence of rational Ritz values. SIAM Journal on Matrix Analysis and Applications, 31 (4): 1740-1774, 2010. [Preprint]  [BibTeX]
  34. M. Afanasjew, M. Eiermann, O. G. Ernst and S. Güttel. A generalization of the steepest descent method for matrix functions. Electronic Transactions on Numerical Analysis, 28: 206-222, 2008. [Preprint]  [BibTeX]
  35. M. Afanasjew, M. Eiermann, O. G. Ernst and S. Güttel. Implementation of a restarted Krylov subspace method for the evaluation of matrix functions. Linear Algebra and its Applications, 429 (10): 2293-2314, 2008. [Preprint]  [BibTeX]

Peer-reviewed conference proceedings

  1. E. Poupard, W. P. Heath and S. Güttel. A Hamiltonian decomposition-based splitting method for interior point solvers in model predictive control. In Proceedings of the 2019 IEEE 58th Conference on Decision and Control, pages 4337-4342, IEEE, 2019. [BibTeX]
  2. M. J. Gander, M. Petcu and S. Güttel. A nonlinear ParaExp algorithm. In Domain Decomposition Methods in Science and Engineering XXIV, pages 261-270, Springer-Verlag, Berlin, 2019. [Preprint]  [BibTeX]
  3. T. D. Butters, S. Güttel, J. L. Shapiro and T. J. Sharpe. Automatic real-time fault detection for industrial assets using metasensors. In Proceedings of the 2015 Asset Management Conference, pages 1-5, The Institute of Engineering and Technology, 2015. [Preprint]  [BibTeX]
  4. T. D. Butters, S. Güttel and J. L. Shapiro. Detecting and reducing redundancy in alarm networks. In Proceedings of the IEEE International Conference on Automation Science and Engineering (CASE), pages 1224-1229, IEEE, 2015. [Preprint]  [BibTeX]
  5. T. D. Butters, S. Güttel, J. L. Shapiro and T. J. Sharpe. Statistical cluster analysis and visualisation for alarm management configuration. In Proceedings of the 2014 Asset Management Conference, pages 1-6, The Institute of Engineering and Technology, 2014. [Preprint]  [BibTeX]
  6. S. Güttel and L. Knizhnerman. Automated parameter selection for rational Arnoldi approximation of Markov functions. In Proceedings in Applied Mathematics and Mechanics (PAMM), pages 15-18, Wiley-VCH Verlag, 2011. [Preprint]  [BibTeX]
  7. S. Güttel. A parallel overlapping time-domain decomposition method for ODEs. In Domain Decomposition Methods in Science and Engineering XX, pages 483-490, Springer-Verlag, Berlin, 2013. [Preprint]  [BibTeX]

Theses

  1. S. Güttel. Rational Krylov Methods for Operator Functions. Ph.D. Thesis, Technische Universität Bergakademie Freiberg, Germany, 2010. [BibTeX]

  1. S. Güttel. Convergence Estimates of Krylov Subspace Methods for the Approximation of Matrix Functions Using Tools from Potential Theory. Master's Thesis, Technische Universität Bergakademie Freiberg, Germany, 2006. [BibTeX]

Technical reports

  1. L. Barash, S. Güttel and I. Hen. Calculating elements of matrix functions using divided differences. Technical Report arXiv:2107.14124, The University of Manchester, UK, 2021. [BibTeX]
  2. R. Cahuantzi, X. Chen and S. Güttel. A comparison of LSTM and GRU networks for learning symbolic sequences. Technical Report arXiv:2107.02248, The University of Manchester, UK, 2021. [BibTeX]
  3. V. Druskin, S. Güttel and L. Knizhnerman. Model order reduction of layered waveguides via rational Krylov fitting. Technical Report 2021.2, The University of Manchester, UK, 2021. [BibTeX]
  4. G. M. Negri Porzio, S. Güttel and F. Tisseur. Robust rational approximations of nonlinear eigenvalue problems. Technical Report 2020.24, The University of Manchester, UK, 2020. [BibTeX]
  5. S. Elsworth and S. Güttel. Time series forecasting using LSTM networks: A symbolic approach. Technical Report arXiv:2003.05672v1, The University of Manchester, UK, 2020. [BibTeX]
  6. M. Berljafa, S. Elsworth and S. Güttel. A Rational Krylov Toolbox for MATLAB. Technical Report 2014.56, The University of Manchester, UK, 2014. [BibTeX]
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Teaching

Course materials are available on Blackboard.
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Other