Mathematical Analysis, Modelling, and Applications

The activity in mathematical analysis is mainly focussed on ordinary and partial differential equations, on dynamical systems, on the calculus of variations, and on control theory. Connections of these topics with differential geometry are also developed.The activity in mathematical modelling is oriented to subjects for which the main technical tools come from mathematical analysis. The present themes are multiscale analysis, mechanics of materials, micromagnetics, modelling of biological systems, and problems related to control theory.The applications of mathematics developed in this course are related to the numerical analysis of partial differential equations and of control problems. This activity is organized in collaboration with MathLab for the study of problems coming from the real world, from industrial applications, and from complex systems.

Home

Subscribe to our mailing list Download the webpage guide

For any questions regarding the website, please contact webmasters at webmaster.math (at) sissa.it.

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

Gianluigi Rozza

Faculty

Andrei Agrachev, Professor
Massimiliano Berti, Professor
Stefano Bianchini, Professor
Andrea Braides, Professor
Ugo Bruzzo, Professor
Ludwik Dabrowski, Professor
Gianni Dal Maso, Professor
Guido De Philippis, Professor
Antonio De Simone, Professor
Gregorio Falqui, Professor
Barbara Fantechi, Professor
Nicola Gigli, Professor
Antonio Lerario, Professor
Marcello Porta, Professor
Gianluigi Rozza, Professor
Jacopo Stoppa, Professor
Alessandro Tanzini, Professor
Andrea Cangiani, Associate Professor
Fabio Cavalletti, Associate Professor
Tamara Grava, Associate Professor
Davide Guzzetti, Associate Professor
Luca Heltai, Associate Professor
Igor Krasovsky, Associate Professor
Alberto Maspero, Associate Professor
Giovanni Noselli, Associate Professor
Luca Rizzi, Associate Professor
Nicolò Sibilla, Associate Professor
Rafael Torres, Associate Professor
Pasquale Claudio Africa, Assistant Professor
Pavlo Gavrylenko, Assistant Professor
Michele Girfoglio, Assistant Professor
Federico Pichi, Assistant Professor
Andrea Tobia Ricolfi, Assistant Professor
Niccolò Tonicello, Assistant Professor
Sandro Zagatti, Assistant Professor
Ricardo Grande Izquierdo, Assistant Professor

Former Faculty Members

Former Professors

Visiting Professors

Rodica Toader, Università di Udine
Andrea Mola, IMT Lucca
Gianfausto Dell'Antonio, Visiting Professor
Giovanni Stabile, Visiting Professor

Area Secretariat

Read more about Home

Wave Kinetic Theory for the Stochastic NLS Equation

Read more about Wave Kinetic Theory for the Stochastic NLS Equation

High Performance Computing for Data Science

The course will utilize a combination of frontal lectures and live programming demonstrations. The course will maintain a balance of approximately 50% frontal lectures and 50% hands-on sessions. The course is designed to be highly interactive, with ample opportunities for students to ask questions and engage in discussions during both the frontal lectures and hands-on sessions. Course materials and further details here.