Talks

1. Quasi-Monte Carlo for Bayesian optimal experimental design problems governed by PDEs. In SIAM Conference on Uncertainty Quantification 2024, Trieste, Italy, February 27, 2024.
2. Doubling the rate for high-dimensional numerical integration. In Finnish Mathematical Days 2024, Aalto University, January 4, 2024.
3. Quasi-Monte Carlo for Bayesian optimal experimental design problems governed by PDEs. In Chemnitz Symposium on Inverse Problems 2023, University of Würzburg, November 9, 2023.
4. Quasi-Monte Carlo methods for Bayesian optimal experimental design problems governed by PDEs. In 11^th Applied Inverse Problems Conference, University of Göttingen, September 7, 2023.
5. Quasi-Monte Carlo approach to Bayesian optimal experimental design. In 10^th International Congress on Industrial and Applied Mathematics, Waseda University, August 25, 2023.
6. On the periodic model of uncertainty quantification with application to inverse problems. In 14^th International Conference on Monte Carlo Methods and Applications, Sorbonne University, June 28, 2023.
7. Quasi-Monte Carlo for optimal control and optimal experimental design problems governed by PDEs. In 9^th Workshop on High-Dimensional Approximation, Australian National University, Canberra, Australia, February 22, 2023.
8. Quasi-Monte Carlo for Bayesian optimal experimental design. In 28^th Inverse Days, University of Eastern Finland, December 14, 2022.
9. Quasi-Monte Carlo methods for optimal control problems subject to parabolic PDE constraints under uncertainty. In 28^th Nordic Congress of Mathematicians, Aalto University, Finland, August 19, 2022.
10. Revisiting the dimension truncation error of parametric elliptic PDEs. In 15^th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, RICAM, Austria, July 18, 2022.
11. Higher-order quasi-Monte Carlo rules for domain uncertainty quantification using periodic random variables. In SIAM Conference on Uncertainty Quantification 2022, Atlanta, USA, April 13, 2022.
12. Modeling domain uncertainty using periodic random variables with application to elliptic PDEs. In SIAM Conference on Imaging Science 2022, Berlin, Germany, March 24, 2022.
13. High-dimensional kernel interpolation over lattice point sets with application to uncertainty quantification. In Finnish Mathematical Days 2022, Tampere University, January 4, 2022.
14. Quasi-Monte Carlo methods for optimal control problems subject to time-dependent PDE constraints under uncertainty. In 27^th Inverse Days, Tampere University, December 16, 2021.
15. On least squares approximation in linear inverse statistical learning problems. In 13^th International Conference on Monte Carlo Methods and Applications, University of Mannheim, August 20, 2021.
16. Quasi-Monte Carlo methods and application to inverse problems. In 26^th Inverse Days, Finnish Meteorological Institute/University of Helsinki, December 17, 2020.
17. Uncertainty quantification using periodic random variables. In ANZIAM 2020, Macquarie University, February 3, 2020.
18. Uncertainty quantification for partial differential equations using periodic random variables. In Finnish Mathematical Days 2020, University of Oulu, January 3, 2020.
19. Uncertainty quantification for PDE-constrained optimal control problems using quasi-Monte Carlo methods. In 25^th Inverse Days, University of Jyväskylä, December 17, 2019.
20. An improved lower bound on Hong and Loewy’s numbers. In 63^rd Annual Meeting of the Australian Mathematical Society, Melbourne, December 6, 2019.
21. Quasi-Monte Carlo methods for uncertainty quantification using periodic random variables. In Uncertainty Quantification Workshop, Australian National University, Canberra, Australia, November 25, 2019.
22. Higher order QMC rules for uncertainty quantification using periodic random variables. In 8^th Workshop on High-Dimensional Approximation, ETH Zurich, September 10, 2019.
23. Uncertainty quantification for stroke EIT imaging using sparse grids. In 24^th Inverse Days, Aalto University, December 11, 2018.
24. Stochastic collocation for electrical impedance tomography with applications to stroke imaging. In Computational Techniques and Applications Conference 2018, Newcastle, Australia, November 28, 2018.
25. Composite surrogate solution of the stochastic planar elasticity problem using sparse grids and measurements. In SIAM Conference on Imaging Science 2018, Bologna, Italy, June 8, 2018.
26. On Hong and Loewy’s numbers and the Ilmonen–Haukkanen–Merikoski numbers. In Finnish Mathematical Days 2018, University of Eastern Finland, January 4, 2018.
27. Computation of extremal eigenvalues of high-dimensional lattice-theoretic tensors in tensor-train format. In 14^th U.S. National Congress on Computational Mechanics, Montreal, Canada, July 19, 2017.
28. On the structure and eigenvalues of lattice-theoretic meet and join tensors. In XI Number Theory Days, University of Tampere, June 5, 2017.
29. Stochastic modulus of a quadrilateral as a benchmark problem for uncertain domains. In SIAM Conference on Uncertainty Quantification 2016, Lausanne, Switzerland, April 5, 2016.
30. Stochastic modulus of a quadrilateral as a benchmark problem for uncertain domains. In Finnish Mathematical Days 2016, University of Turku, January 7, 2016.