MaLGa logoMaLGa black extendedMaLGa white extendedUniGe ¦ MaLGaUniGe ¦ MaLGaUniversita di Genova | MaLGaUniversita di Genova
News

Giovanni Alberti's "Sample complexity for inverse problems in PDE” wins ERC Starting Grant

22/04/2022

Giovanni S. Alberti vince un ERC

We are proud to announce that the European Research Council has approved another project presented by a MaLGa researcher: Giovanni S. Alberti, member of MaLGa’s faculty and researcher at the Department of Mathematics of UniGe, has been awarded an ERC Starting Grant 2021 of 1.2 million Euros for his project titled "Sample complexity for inverse problems in PDE". 


The main aspect of the project lies in combining different fields of mathematics: on the one hand, the study of mathematical models based on partial differential equations for the description of various physical phenomena and, on the other hand, the analysis of signals through the use of information theory and machine learning. Although it has not yet been fully explored, the interaction between these research areas is quite natural, as the physical quantities of the models based on PDE can also be seen as signals to be analyzed with methods of applied harmonic analysis and machine learning. Thanks to the combination of these techniques, it will be possible to study the sample complexity of inverse problems in PDE, in which certain physical quantities must be reconstructed from few indirect measurements.

 

Giovanni S. Alberti, born in 1987, is a researcher at the Department of Mathematics of the University of Genoa and a member of MaLGa’s faculty. After his PhD from the University of Oxford, Prof. Alberti held two postdoctoral positions at the École Normale Supérieure in Paris and at the ETH in Zürich. His research focuses on PDE, applied harmonic analysis and their interactions with inverse problems, machine learning and imaging. He won the Gioacchino Iapichino Award for Mathematical Analysis in 2017, the Eurasian Association on Inverse Problems Young Scientist Award for his contribution to inverse problems in 2018 and was selected among the emerging talents of 2021 by the journal Inverse Problems.