Vesa Kaarnioja, D.Sc. (Tech.)
LUT University
School of Engineering Sciences
P.O. Box 20, 53851 Lappeenranta, Finland

Publications

Submitted manuscripts
  1. A. Djurdjevac, V. Kaarnioja, C. Schillings, and A.-A. Zepernick. Uncertainty quantification for stationary and time-dependent PDEs subject to Gevrey regular random domain deformations.
Peer-reviewed articles
  1. V. Kaarnioja, A. Rupp, and J. Gopalakrishnan. Sufficient conditions for QMC analysis of finite elements for parametric differential equations. Accepted for publication in SIAM/ASA Journal on Uncertainty Quantification, 2026.
  2. V. Kaarnioja and C. Schillings. Quasi-Monte Carlo for Bayesian design of experiment problems governed by parametric PDEs. Numerische Mathematik, published online, 45 pp., 2026.
  3. P. A. Guth and V. Kaarnioja. On the optimality of dimension truncation error rates for a class of parametric partial differential equations. In: Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control (EUROGEN 2025), J. Hämäläinen, M. Amadi, N. Gauger, K. Giannakoglou, J. Periaux (eds.), Springer, pp. 432-441, 2026.
  4. A. Djurdjevac, V. Kaarnioja, M. Orteu, and C. Schillings. Quasi-Monte Carlo for Bayesian shape inversion governed by the Poisson problem subject to Gevrey regular domain deformations. In: Monte Carlo and Quasi-Monte Carlo 2024, C. Lemieux and B. Feng (eds.), Springer, pp. 239-257, 2026.
  5. V. Kaarnioja, I. Klebanov, C. Schillings, and Y. Suzuki. Lattice rules meet kernel cubature. In: Monte Carlo and Quasi-Monte Carlo 2024, C. Lemieux and B. Feng (eds.), Springer, pp. 277-295, 2026.
  6. V. Kaarnioja and A.-A. Zepernick. New upper and lower bounds on the smallest singular values of nonsingular lower triangular (0,1)-matrices. Linear Algebra and its Applications 730, 483-497, 2026.
  7. P. A. Guth and V. Kaarnioja. Quasi-Monte Carlo for partial differential equations with generalized Gaussian input uncertainty. SIAM Journal on Numerical Analysis 63(4), 1666-1690, 2025.
  8. L. Bazahica, V. Kaarnioja, and L. Roininen. Uncertainty quantification for electrical impedance tomography using quasi-Monte Carlo methods. Inverse Problems 41, 065002, 2025.
  9. I. H. Sloan and V. Kaarnioja. Doubling the rate: improved error bounds for orthogonal projection with application to interpolation. BIT Numerical Mathematics 65, 10, 2025.
  10. V. Kaarnioja. Explicit solutions of Genz test integrals. Applied Mathematics Letters 163, 109444, 2025.
  11. V. Kaarnioja and A. Rupp. Quasi-Monte Carlo and discontinuous Galerkin. Electronic Transactions on Numerical Analysis 60, 589-617, 2024.
  12. V. Kaarnioja, F. Y. Kuo, and I. H. Sloan. Lattice-based kernel approximation and serendipitous weights for parametric PDEs in very high dimensions. In: Monte Carlo and Quasi-Monte Carlo Methods 2022, A. Hinrichs, P. Kritzer, F. Pillichshammer (eds.), Springer, pp. 81-103, 2024.
  13. P. A. Guth and V. Kaarnioja. Application of dimension truncation error analysis to high-dimensional function approximation in uncertainty quantification. In: Monte Carlo and Quasi-Monte Carlo Methods 2022, A. Hinrichs, P. Kritzer, F. Pillichshammer (eds.), Springer, pp. 297-312, 2024.
  14. P. A. Guth and V. Kaarnioja. Generalized dimension truncation error analysis for high-dimensional numerical integration: lognormal setting and beyond. SIAM Journal on Numerical Analysis 62(2), 872-892, 2024.
  15. P. A. Guth, V. Kaarnioja, F. Y. Kuo, C. Schillings, and I. H. Sloan. Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration. Numerische Mathematik 156, 565-608, 2024.
  16. H. Hakula, H. Harbrecht, V. Kaarnioja, F. Y. Kuo, and I. H. Sloan. Uncertainty quantification for random domains using periodic random variables. Numerische Mathematik 156, 273-317, 2024.
  17. V. Kaarnioja, Y. Kazashi, F. Y. Kuo, F. Nobile, and I. H. Sloan. Fast approximation by periodic kernel-based lattice-point interpolation with application in uncertainty quantification. Numerische Mathematik 150, 33-77, 2022.
  18. P. A. Guth, V. Kaarnioja, F. Y. Kuo, C. Schillings, and I. H. Sloan. A quasi-Monte Carlo method for optimal control under uncertainty. SIAM/ASA Journal on Uncertainty Quantification 9(2), 354-383, 2021.
  19. V. Kaarnioja. Bounds on the spectrum of nonsingular triangular (0,1)-matrices. Journal of Combinatorial Theory, Series A 178, 105353, 2021.
  20. V. Kaarnioja, F. Y. Kuo, and I. H. Sloan. Uncertainty quantification using periodic random variables. SIAM Journal on Numerical Analysis 58(2), 1068-1091, 2020.
  21. H. Hakula, V. Kaarnioja, and M. Laaksonen. Cylindrical shell with junctions: uncertainty quantification of free vibration and frequency response analysis. Shock and Vibration, vol. 2018, Article ID 5817940, 16 pp., 2018.
  22. P. Ilmonen and V. Kaarnioja. Generalized eigenvalue problems for meet and join matrices on semilattices. Linear Algebra and its Applications 536, 250-273, 2018.
  23. N. Hyvönen, V. Kaarnioja, L. Mustonen, and S. Staboulis. Polynomial collocation for handling an inaccurately known measurement configuration in electrical impedance tomography. SIAM Journal on Applied Mathematics 77, 202-223, 2017.
  24. H. Hakula, V. Kaarnioja, and M. Laaksonen. Approximate methods for stochastic eigenvalue problems. Applied Mathematics and Computation 267, 664-681, 2015.
Theses