Academic Publications
Journal Articles
Fractional Sobolev spaces related to an ultraparabolic operator 2025Antonello Pesce, Sascha Portaro Springer Journal of Evolution Equations Vol. 25, Issue 3.
Row-Aware Randomized SVD With Applications 2026
Davide Palitta, Sascha Portaro Wiley Numerical Linear Algebra with Applications Vol. 33, Issue 3.
Submitted Papers
A Practical Mode-parallel Implementation of the (H-)Tucker Decomposition via Randomization
Martina Iannacito, Sascha Portaro, Davide Palitta, Claudio Arlandini, Domitilla Brandoni (2026). Preprint, arXiv:2603.21379.
Numerical methods for Langevin-type SPDE: an implicit Milstein approach and multilevel Monte Carlo techniques
Sascha Portaro, Carlos Vázquez Cendón. In preparation; arXiv preprint forthcoming.
International Research Experiences
International collaboration plays a central role in my research, fostering the exchange of ideas across applied mathematics, scientific computing, and numerical analysis. Working with researchers from different institutions and countries allows me to combine complementary expertise and develop mathematical methods with broad scientific impact.
Visiting period, University of A Coruña, Spain (25/02/2025 - 03/06/2025)
Research stay under the supervision of Prof. Carlos Vázquez Cendón, focused on numerical methods for stochastic partial differential equations (SPDEs). Developed and analysed an implicit Milstein finite difference scheme for degenerate Langevin-type models, proving stability and convergence results. Investigated Multilevel Monte Carlo methods for efficient uncertainty quantification and validated the theoretical analysis through numerical experiments.Semester Program at ICERM, Brown University, USA (19/01/2026 - 26/04/2026)
Visiting research period at the Institute for Computational and Experimental Research in Mathematics (ICERM), Brown University, as part of the semester program Stochastic and Randomized Algorithms in Scientific Computing: Foundations and Applications. The program focused on randomized numerical linear algebra, probabilistic methods, Bayesian inverse problems, and stochastic optimization, with emphasis on rigorous error analysis, statistical guarantees, and scalable computational methods for scientific applications.Conference & Workshop Presentations
I regularly present my research at international conferences, specialized workshops, and thematic meetings in numerical analysis, scientific computing, and applied mathematics. These presentations provide an opportunity to disseminate new research results, exchange ideas with the scientific community, and receive valuable feedback that contributes to the development of my work
Invited & Contributed Talks
23/05/2024 - 23/05/2024 Bologna, Italy
SCUBE Seminar Series
Presentation of research results on randomized numerical linear algebra, introducing
Row-aware Randomized SVD (R-RSVD) and its subsampled variant (Rsub-RSVD) for efficient low-rank matrix approximations with theoretical guarantees and applications to CUR decompositions and reduced-order modelling.
23/09/2024 - 24/09/2024 Göttingen, Germany
GAMM Workshop on Applied and Numerical Linear Algebra 2024
Delivered a contributed talk presenting the Row-Aware Randomized SVD algorithm, its theoretical foundations, numerical performance, and applications to low-rank approximation and model reduction.
07/01/2026 - 09/01/2026 Leuven, Belgium
METT XI - 11th Workshop on Matrix Equations and Tensor Techniques
Delivered a contributed talk presenting our work on randomized mode-parallel Tucker and Hierarchical Tucker decompositions for large-scale tensor computations.
Poster Presentations
31/08/2025 - 05/09/2025 Cortona, Italy
INdAM Workshop: Low-rank Structures and Numerical Methods in Matrix and Tensor Computations
Presented a research poster on the development of randomized mode-parallel algorithms for Tucker and Hierarchical Tucker tensor decompositions.
02/02/2026 - 06/02/2026 Providence, Rhode Island, USA
Randomized Numerical Linear Algebra
Presented a poster on randomized low-rank tensor approximation methods and their parallel implementations, developed within the ICERM semester program "Stochastic and Randomized Algorithms in Scientific Computing: Foundations and Applications" at Brown University.