Bakgrunn og aktiviteter
Elena Celledoni has been employed at the Department of Mathematical Sciences since 2004. She is a professor of mathematics since 2009. She is a member and currently the leadre of the group of differential equations and numerical analysis.
She received her Master degree in mathematics from the University of Trieste in 1993, and her Ph.D in computational mathematics from the University of Padua, Italy, 1997. She held post doc positions at the University of Cambridge, UK, at the
Mathematical Sciences Research Institute, Berkeley, California and at NTNU.
Her research field is in numerical analysis and in particular structure preserving algorithms for differential equations and geometric numerical integration.
Recent video on shape analysis
Vitenskapelig, faglig og kunstnerisk arbeid
Et utvalg av nyere tidsskriftspublikasjoner, kunstneriske produksjoner, bok, inklusiv bokdeler og rapport-del. Se alle publikasjoner i databasen
- (2021) An integral model based on slender body theory, with applications to curved rigid fibers. Physics of Fluids. vol. 33 (4).
- (2021) Structure preserving deep learning. European journal of applied mathematics.
- (2019) Deep learning as optimal control problems: models and numerical methods. Journal of Computational Dynamics. vol. 6 (2).
- (2019) Energy-preserving methods on Riemannian manifolds. Mathematics of Computation. vol. 89 (322).
- (2019) Discrete Darboux polynomials and the search for preserved measures and integrals of rational maps. arXiv.org.
- (2019) Using discrete Darboux polynomials to detect and determine preserved measures and integrals of rational maps. Journal of Physics A: Mathematical and Theoretical. vol. 52 (31).
- (2019) Using discrete Darboux polynomials to detect and determine preserved measures and integrals of rational maps. arXiv.org.
- (2019) Energy-Preserving Integrators Applied to Nonholonomic Systems. Journal of nonlinear science. vol. 29 (4).
- (2019) Predicting bending moments with machine learning. Lecture Notes in Computer Science (LNCS). vol. LNCS11712.
- (2019) Signatures in Shape analysis: An efficient approach to motion identification. Lecture Notes in Computer Science (LNCS). vol. 11712 LNCS.
- (2019) Geometric and integrability properties of Kahan?s method: The preservation of certain quadratic integrals. Journal of Physics A: Mathematical and Theoretical. vol. 52 (6).
- (2019) Krylov projection methods for linear Hamiltonian systems. Numerical Algorithms.
- (2019) A novel approach to rigid spheroid models in viscous flows using operator splitting methods. Numerical Algorithms. vol. 81 (4).
- (2019) Computational methods for tracking inertial particles in discrete incompressible flows. arXiv.org.
- (2019) Three classes of quadratic vector fields for which the Kahan discretization is the root of a generalised Manin transformation. Journal of Physics A: Mathematical and Theoretical. vol. 52 (4).
- (2018) Dissipative numerical schemes on Riemannian manifolds with applications to gradient flows. SIAM Journal on Scientific Computing. vol. 40 (6).
- (2018) Shape analysis on homogeneous spaces: a generalised SRVT framework. Abel Symposia. vol. 13.
- (2018) Passivity-preserving splitting methods for rigid body systems. Multibody system dynamics. vol. 44 (3).
- (2018) A novel approach to rigid spheroid models in viscous flows using operator splitting methods. arXiv.org.
- (2017) Shape analysis on Lie groups and homogeneous manifolds. Proceedings of the GSI conference 2017.