Education and early career

​Stefano Zampini earned his PhD in Computational Mathematics from the University of Milan in 2010. His work mainly focuses on non-overlapping domain decomposition preconditioners of the dual-primal type (namely, BDDC and FETI-DP type methods) for solving large and sparse linear systems arising from finite elements discretizations and IsoGeometric Analysis. In the past, he worked for the italian Supercomputing center CINECA, with a specific interest in optimization and parallelization of oil and gas applications, and for the italian weather forecast agency.

Research Interests

Dr. Zampini focuses his work on highly heterogeneous linear systems, including those of saddle point type arising from Darcy' equations and on electro-magnetics inversion problems. He is currently an active developer of the award winner PETSc library, developed at the Mathematics and Computer Science Division of the Argonne National Laboratory.

Selected Publications

Pavarino, L. F., Scacchi, S., Widlund, O. B., & Zampini, S. (2018). Isogeometric BDDC deluxe preconditioners for linear elasticity. Mathematical Models and Methods in Applied Sciences, 28(07), 1337–1370. doi:10.1142/s0218202518500367
Chávez, G., Turkiyyah, G., Zampini, S., & Keyes, D. (2018). Parallel accelerated cyclic reduction preconditioner for three-dimensional elliptic PDEs with variable coefficients. Journal of Computational and Applied Mathematics, 344, 760–781. doi:10.1016/
Zampini, S., & Tu, X. (2017). Multilevel Balancing Domain Decomposition by Constraints Deluxe Algorithms with Adaptive Coarse Spaces for Flow in Porous Media. SIAM Journal on Scientific Computing, 39(4), A1389–A1415. doi:10.1137/16m1080653
Zampini, S. (2016). PCBDDC: A Class of Robust Dual-Primal Methods in PETSc. SIAM Journal on Scientific Computing, 38(5), S282–S306. doi:10.1137/15m1025785
Zampini, S., & Keyes, D. E. (2016). On the Robustness and Prospects of Adaptive BDDC Methods for Finite Element Discretizations of Elliptic PDEs with High-Contrast Coefficients. Proceedings of the Platform for Advanced Scientific Computing Conference on - PASC ’16. doi:10.1145/2929908.2929919