Prof. Dr. Stefan Güttel

My main research interests are in computational mathematics, including numerical algorithms for large-scale problems arising with differential equations and in data science. A short CV is available as PDF.

Brief academic CV

• 2021– Professor of Applied Mathematics
• 2021 SIAM James H. Wilkinson Prize in Numerical Analysis & Scientific Computing
• 2018 University Teaching Excellence Award
• 2018– Fellow of the Turing Institute
• 2012–2021 Lecturer, Senior Lecturer, Reader at University of Manchester
• 2011–2012 Postdoc at University of Oxford (DFG stipend)
• 2010–2011 Postdoc at University of Geneva
• 2008 JSPS Fellow at National Institute of Informatics in Japan
• 2006–2010 PhD (Dr. rer. nat., summa cum laude) at TU Freiberg
• 2001–2006 Applied Maths (Dipl.-Math.) at TU Bergakademie Freiberg

Current roles

• Associate Editor for SIAM Journal on Scientific Computing
• Associate Editor for Electronic Transactions on Numerical Analysis
• Member of the SIAM Membership Committee and its EDI subcommittee

Current projects

• 01/2020–06/2022 Next generation software for structural engineering simulation, Innovate UK, £352,190

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.)

Articles in peer-reviewed journals

1. X. Chen and S. Güttel. An efficient aggregation method for the symbolic representation of temporal data. Accepted for publication in ACM Transactions on Knowledge Discovery from Data, 2022. [BibTeX]
2. G. M. Negri Porzio, S. Güttel and F. Tisseur. Robust rational approximations of nonlinear eigenvalue problems. Accepted for publication in SIAM Journal on Scientific Computing, 2022. [BibTeX]
3. V. Druskin, S. Güttel and L. Knizhnerman. Model order reduction of layered waveguides via rational Krylov fitting. Accepted for publication in BIT Numerical Mathematics, 2022. [BibTeX]
4. L. Barash, S. Güttel and I. Hen. Calculating elements of matrix functions using divided differences. Computer Physics Communications, 271: 108219, 2021. [Preprint]  [BibTeX]
5. 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]
6. 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]
7. 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]
8. 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]
9. S. Güttel, D. Kressner and K. Lund. Limited-memory polynomial methods for large-scale matrix functions. GAMM-Mitteilungen, 43 (4): e202000019, 2020. [Preprint]  [BibTeX]
10. 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]
11. S. Elsworth and S. Güttel. The block rational Arnoldi method. SIAM Journal on Matrix Analysis and Applications, 41 (2): 365-388, 2020. [Preprint]  [BibTeX]
12. 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]
13. 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]
14. 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]
15. 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]
16. M. Berljafa and S. Güttel. The RKFIT algorithm for nonlinear rational approximation. SIAM Journal on Scientific Computing, 39 (5): A2049-A2071, 2017. [Preprint]  [BibTeX]
17. M. Berljafa and S. Güttel. Parallelization of the rational Arnoldi algorithm. SIAM Journal on Scientific Computing, 39 (5): S197-S221, 2017. [Preprint]  [BibTeX]
18. S. Güttel and F. Tisseur. The nonlinear eigenvalue problem. Acta Numerica, 26: 1-94, 2017. [Preprint]  [BibTeX]
19. 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]
20. 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]
21. 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]
22. 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]
23. 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]
24. 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]
25. 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]
26. 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]
27. 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]
28. 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]
29. S. Güttel and J. Pestana. Some observations on weighted GMRES. Numerical Algorithms, 67 (4): 733-752, 2014. [Preprint]  [BibTeX]
30. S. Güttel. Rational Krylov approximation of matrix functions: Numerical methods and optimal pole selection. GAMM-Mitteilungen, 36 (1): 8-31, 2013. [Preprint]  [BibTeX]
31. 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]
32. P. Gonnet, S. Güttel and L. N. Trefethen. Robust Padé approximation via SVD. SIAM Review, 55 (1): 101-117, 2013. [Preprint]  [BibTeX]
33. 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]
34. 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]
35. 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]
36. 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]
37. 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]
38. 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]
39. 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

40. X. Chen and S. Güttel. A fast sorting-based aggregation method for symbolic time series representation. In Proceedings of the 2021 International Conference on Data Mining Workshops (ICDMW), pages 1009-1016, IEEE, 2021. [BibTeX]
41. 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]
42. 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]
43. 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]
44. 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]
45. 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]
46. 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]
47. 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

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

49. 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

50. X. Chen and S. Güttel. Fast and explainable clustering based on sorting. Technical Report arXiv:2202.01456, The University of Manchester, UK, 2022. [BibTeX]
51. K. Oster, S. Güttel, J. L. Shapiro, Lu Chen and M. Jobson. Pre-treatment of outliers and anomalies in plant data: Methodology and case study of a Vacuum Distillation Unit. Technical Report arXiv:2106.14641, The University of Manchester, UK, 2021. [BibTeX]
52. 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]
53. 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]
54. M. Berljafa, S. Elsworth and S. Güttel. A Rational Krylov Toolbox for MATLAB. Technical Report 2014.56, The University of Manchester, UK, 2014. [BibTeX]

• MATH20411 PDEs and Vector Calculus B (semester 1)
• MATH20621 Programming with Python (semester 1)
• MATH65740 Introduction to MATLAB (semester 1)
• MATH19662 Mathematics 1M2 for Civil Engineers (semester 2)
• MATH19872 Mathematics 0D2 Foundation (semester 2)

Course materials are available on Blackboard.

• Rational Krylov Toolbox for MATLAB
  A MATLAB toolbox developed with my PhD students.
• PARTYMAT.DE
  A German event management system I develop and run, and its UK version.
• Flickr photos
  I enjoy taking photos of Manchester and on travel.
• INEGO
  I play the electric bass in an alternative rock band.