Talks

  1. Sampling for sparsity-promoting hierarchical Bayesian models using prior normalization.
    SIAM UQ24, Trieste (Italy), February 2024.

  2. A new perspective on the stability of radial basis function methods using summation-by-parts operators.
    Department of Mathematics, Pennsylvania State University, State College, PA (USA), February 2024.

  3. A new perspective on the stability of radial basis function methods using summation-by-parts operators.
    Institute of Mathematics, Clausthal University of Technology, Clausthal-Zellerfeld (Germany), January 2024.

  4. Sparsity-promoting hierarchical Bayesian learning for inverse problems.
    Numerical Methods for PDEs Seminar, MIT Mathematics Department, Cambridge, MA (USA), November 2023.

  5. Beyond the conventional: Stable and innovative approaches to advection-dominated problems.
    Numerical Analysis Symposium, University Hamburg, Hamburg (Germany), October 2023.

  6. Stability of radial basis function methods for hyperbolic conservation laws.
    CASUS workshop "Numerical differential geometry and kernel methods”, Görlitz (Germany), September 2023.

  7. Sparsity-promoting hierarchical Bayesian inverse problems and uncertainty quantification.
    11th AIP conference, Göttingen (Germany), September 2023.

  8. The power of joint sparsity: A hierarchical Bayesian learning approach.
    SCALES Conference, Mainz (Germany), June 2023.
    (DOI: 10.13140/RG.2.2.11156.07041)

  9. A new perspective on the stability of RBF methods for conservation laws.
    AMS Spring Central Sectional Meeting, Cincinnati (OH, USA), April 2023.

  10. A new perspective on the stability of RBF methods for conservation laws.
    SIAM CSE, Amsterdam (Netherlands), February 2023.
    (DOI: 10.13140/RG.2.2.13033.36962)

  11. Better together: The partnership of numerical analysis and Bayesian inference.
    MIT Aerospace Computational Design Laboratory Seminar Series, Cambridge, MA (USA), October 2022.

  12. Generalized sparse Bayesian learning with uncertainty quantification.
    SIMDA MURI Annual Meeting, virtual, October 2022.

  13. Beyond polynomials: SBP operators for general function spaces.
    XVIII International Conference on Hyperbolic Problems, Malaga (Spain), June 2022.
    (DOI: 10.13140/RG.2.2.30025.01122)

  14. Sparse Bayesian image reconstruction: Towards a unified approach.
    SIAM Conference on Imaging Science, virtual, March 2022.

  15. Sparse Bayesian learning for image reconstruction with uncertainty quantification.
    AFOSR 2022 Annual EM Portfolio Review, virtual, January 2022.

  16. Least Squares Formulas - The Swiss Army Knife of Numerical Integration?.
    SIAM Annual Meeting, virtual, July 2021.
    (DOI: 10.13140/RG.2.2.35921.45926)

  17. High Order Edge Sensors with l1 Regularization for Enhanced Discontinuous Galerkin Methods.
    ICOSAHOM 2020, virtual, July 2021.
    (DOI: 10.13140/RG.2.2.16594.89284)

  18. Numerical integration of experimental data.
    7th Heidelberg Laureate Forum, Heidelberg (Germany), September 2019.

  19. Shock capturing in high-order methods for conservation laws.
    Oberseminares “Numerik und Optimierung”, Heinrich-Heine University, Düsseldorf (Germany), October 2018.

  20. High order edge sensors with l1 regularisation for enhanced discontinuous Galerkin methods.
    Advances in PDEs: Theory, Computation, and Application to CFD, ICERM, Providence, RI (USA), August 2018.

  21. The principle of discrete least squares in spectral element approximations.
    XVII International Conference on Hyperbolic Problems, University Park, Pennsylvania (USA), June 2018.

  22. Application of discrete least squares approximations to PDE solvers.
    39th Northern German Colloquium on Applied Analysis and Numerical Mathematics, Braunschweig (Germany), June 2018.

  23. A novel discontinuous Galerkin method using the principle of discrete least squares.
    Numerical analysis group internal seminar, Oxford (UK), October 2017.

  24. How to overcome the Gibbs phenomenon? Modal and nodal filtering.
    Conference on Recent Advances in Analysis and Numerics of Hyperbolic Conservation Laws, Magdeburg (Germany), September 2016.

  25. Modal filtering for CPR methods using SBP operators.
    XVI International Conference on Hyperbolic Problems, Aachen (Germany), August 2016.

  26. Nodal filtering: How to overcome the Gibbs phenomenon?.
    DMV Students’ Conference 2016, Berlin (Germany), July 2016.

  27. Nodal filtering in spectral methods.
    37th Northern German Colloquium on Applied Analysis and Numerical Mathematics, Lu ̈beck (Germany), April 2016.