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Research fields

geometry, in particular algebraic, differential, and noncommutative geometry, also with applications to quantum field and string theory
mathematical analysis, in particular calculus of variations, control theory, partial and ordinary differential equations
mathematical modelling, in particular mechanics of solids and fluids, modelling of complex and biological systems, multiscale analysis
mathematical physics, in particular integrable systems and their applications, nonlinear partial differential equations, mathematical aspects of quantum physics
numerical analysis and scientific computing, applied to partial differential equations and to control problems

PhD and MSC courses:

Geometry and Mathematical Physics
Mathematical Analysis, Modelling, and Applications
MSc in Mathematics (Laurea Magistrale in Matematica) in collaboration with the University of Trieste
Master Degree in Data Science and Scientific Computing in collaboration with the Universities of Trieste and Udine, and with ICTP
Joint SISSA-ICTP professional Master in High Performance Computing (MHPC)

Laboratories:

SISSA MathLab: a laboratory for mathematical modeling and scientific computing
SAMBA a laboratory in collaboration with the Cognitive Neuroscience Group

Area Coordinator

Antonio Lerario

Faculty

Massimiliano Berti, Professor
Stefano Bianchini, Professor
Antonio De Simone, Professor
Barbara Fantechi, Professor
Nicola Gigli, Professor
Antonio Lerario, Professor
Alberto Maspero, Professor
Giovanni Noselli, Professor
Marcello Porta, Professor
Luca Rizzi, Professor
Gianluigi Rozza, Professor
Jacopo Stoppa, Professor
Alessandro Tanzini, Professor
Gabriele Benedetti, Associate Professor
Mikhail Bershtein, Associate Professor
Andrea Cangiani, Associate Professor
Ilya Chevyrev, Associate Professor
Tamara Grava, Associate Professor
Davide Guzzetti, Associate Professor
Igor Krasovsky, Associate Professor
Gaultier Lambert, Associate Professor
Andrea Ricolfi, Associate Professor
Nicolò Sibilla, Associate Professor
Rafael Torres, Associate Professor
Pasquale Claudio Africa, Assistant Professor
Antonio Colanera, Assistant Professor
Pavlo Gavrylenko, Assistant Professor
Ricardo Grande Izquierdo, Assistant Professor
Federico Pichi, Assistant Professor
Davide Riccobelli, Assistant Professor
Niccolò Tonicello, Assistant Professor

Former Faculty Members

Former Professors

Visiting Professors

Andrei Agrachev, Visiting Professor
Andrea Braides, Visiting Professor
Gianfausto Dell'Antonio, Visiting Professor
Andrea Mola, IMT Lucca
Maria Giovanna Mora, Università di Pavia
Rodica Toader, Università di Udine

Area Secretariat

Read more about Home

Advanced reduced order models in scientific machine learning

This course aims to provide a wide overview on novel strategies combining ideas from Reduced Order Modeling (ROM) and Scientific Machine Learning (SciML). The main goal is to investigate the great potential and the possible limitations of state-of-the-art methodologies to efficiently retrieve solutions of parametrized PDEs for computational mechanics problems.

Read more about Advanced reduced order models in scientific machine learning

Computational Mechanics by Reduced order methods

Learning outcomes and objectives

The course aims to provide the basic aspects of numerical approximation and efficient solution of parametrized PDEs for computational mechanics problem (heat and mass transfer, linear elasticity, viscous and potential flows) using reduced order methods.