News:

• Check our latest preprint on risk-averse optimization combining importance sampling with reduced order models!

• Looking forward to attend ENUMATH25 in Heidelberg and EUCCO in Klagenfurt.

• Join us for the workshop on "Multifidelity Methods for Stochastic and Uncertain Problems" to be held in Bonn in early February 2026! Have a look here for additional information!

About

I am currently an assistant professor with time contract (RTD/A) at Politecnico di Torino.

Previously, I was a postdoctoral researcher in the CSQI (Calcul scientifique et quantification de l'incertitude) Chair led by Prof. Nobile at EPFL.

I discussed my doctoral thesis elaborated under the supervision of  Prof. Martin J. Gander  at the University of Geneva in September 2020.

Students

I am always looking for motivated students for bachelor, master thesis or parallel research projects. Broad topics are: iterative methods, optimization algorithms, uncertainty quantification, manifolds and machine learning. Don't hesitate to get in contact by sending an email!

Publications

Submitted manuscripts:

• S. Pieraccini, T. Vanzan, An adaptive importance sampling algorithm for risk-averse optimization 

• G. Ciaramella, M. Gander, T. Vanzan, S. Van Criekingen, Algebraic and two-level parallel substructured Schwarz methods.

Refereed Journal Publications:

• F. Nobile, T. Vanzan, Multilevel quadrature formulae for the optimal control of random PDEs, to appear in Numerische Mathematik.

• G. Ciaramella, M.J. Gander, T. Vanzan, A gentle introduction to interpolation on the Grassmann manifold, to appear in SIAM Review. 

• G. Ciaramella, F. Nobile, T. Vanzan, A multigrid method for PDE-constrained optimization with uncertain inputs, Vol. 101, Journal of Scientific Computing, 2024.

• F. Nobile, T. Vanzan, A combination technique for optimal control problems constrained by random PDEs, SIAM/ASA Journal on Uncertainty Quantification, Vol. 12, N.2, 2024.

• M. Gamberini, G. Ciaramella, E. Miglio, T. Vanzan, Robust optimization of control parameters for WEC arrays using stochastic optimization, J. Comp. Physics, Vol 493, 2023.

• M. DIscacciati, T. Vanzan, Optimized Schwarz methods for the time-dependent Stokes-Darcy coupling, IMA Journal of Numerical Analysis, 2023.

• F.Nobile, T. Vanzan, Preconditioners for robust optimal control problems under uncertainty, Numerical Linear Algebra with Applications, Vol.30, Issue 2, 2023.

• G. Ciaramella, T. Vanzan, Spectral coarse spaces for the substructured parallel Schwarz method, Journal of Scientific Computing, 2022.

• G. Ciaramella, T. Vanzan, Substructured two-grid and multi-grid domain decomposition methods, Numerical Algorithms, 2022.

• F. Chaouqui, M.J. Gander, P. M. Kumbhar, T. Vanzan, Linear and nonlinear substructured restricted additive Schwarz iterations and preconditioning, accepted in Numerical Algorithms, 2022.

• M.J. Gander, T. Vanzan, Multilevel Optimized Schwarz Methods , SIAM Journal on Scientific Computing, 42 (5), A3180–A3209, 2020.

• M.J. Gander, T. Vanzan, Heterogeneous optimized Schwarz methods for second order elliptic PDEs , SIAM Journal on Scientific Computing, 41 (4), A2329-A2354, 2019.

• F. Chaouqui, G. Ciaramella, M.J. Gander, T. Vanzan, On the scalability of classical one-level domain-decomposition methods , Vietnam Journal of Mathematics, Vol. 46, No. 4, pp. 1053--1088, 2018.

• T. Vanzan, L. Rondoni, Quantum thermostatted disordered systems and sensitiviy under compression , Physica A: Statistical Mechanics and its Applications, Volume 493, Pages 370-383, 2018.

Refereed Conference Proceedings :

• M. Sutti, T. Vanzan, Nonlinear Schwarz methods to compute geodesics on manifolds, to appear in Domain Decomposition Methods in Science and Engineering XXVIII.

• G. Ciaramella, T. Vanzan, Variable reduction as a nonlinear preconditioning approach for optimization problems, to appear in Domain Decomposition Methods in Science and Engineering XXVIII.

• M.J. Gander, J. Hennicker, R. Masson, T. Vanzan, Dimensional reduction by Fourier analysis of a Stokes-Darcy fracture model, in Finite Volumes for Complex Applications XI - Methods, Theoretical Aspects, Examples. FVCA 2023.

• S. Berrone, T. Vanzan, Weak scalability of domain decomposition methods for discrete fracture networks,  in  Domain Decomposition Methods in Science and Engineering XXVII.

• G. Ciaramella, M. J. Gander, T. Vanzan, S. Van Criekingen, A Performance Comparison of Classical Volume and New Substructured One- and Two-level Schwarz Methods in PETSc, in Domain Decomposition Methods in Science and Engineering XXVII.

• M.J. Gander, R. Masson, T. Vanzan, A numerical algorithm based on probing to find optimized transmission conditions, in Domain Decomposition Methods in Science and Engineering XXVI, pp 597–605, 2023.

• F. Chaouqui, M.J. Gander, P.M. Kumbhar, T. Vanzan, On the nonlinear Dirichlet-Neumann method and preconditioner for Newton's method, in Domain Decomposition Methods in Science and Engineering XXVI, pp 381–389, 2023.

• G. Ciaramella, T. Vanzan, On the asymptotic optimality of spectral coarse spaces, in Domain Decomposition Methods in Science and Engineering XXVI, pp 187–195, 2023.

• M.J. Gander, T. Vanzan, On the derivation of optimized transmission conditions for the Stokes-Darcy coupling , in Domain Decomposition Methods in Science and Engineering XXV, Pages 491-498, 2020.

• M.J. Gander, T. Vanzan, Heterogeneous optimized Schwarz methods for coupling Helmholtz and Laplace equations , in Domain Decomposition Methods in Science and Engineering XXIV, Pages 311--320, 2018.

• M.J. Gander, T. Vanzan, Optimized Schwarz methods for advection diffusion equations in bounded domains , in Proceedings of ENUMATH2017, Pages 921-929, 2018.

Doctoral thesis:

• T. Vanzan, Domain decomposition methods for multiphysics problems, University of Geneva, 2020.

Software

GDGMatlab contains libraries to implement Finite element methods (FEM) and Discontinous Galerking finite element methods (DG) for the solution of partial differential equations in Matlab. The codes are available on Github