Academic Career and Research Areas
The research of Massimo Fornasier embraces a broad spectrum of problems in mathematical modeling, analysis and numerical analysis. Fornasier is particularly interested in the concept of compression as appearing in different forms in data analysis, image and signal processing, and in the adaptive numerical solutions of partial differential equations or high-dimensional optimization problems.
Fornasier received his doctoral degree in computational mathematics in 2003 from the University of Padua, Italy. After spending from 2003 to 2006 as a postdoctoral research fellow at the University of Vienna and University of Rome La Sapienza, he joined the Johann Radon Institute for Computational and Applied Mathematics (RICAM) of the Austrian Academy of Sciences where he served as a senior research scientist until March 2011. He was an associate researcher from 2006 to 2007 for the Program in Applied and Computational Mathematics of Princeton University, USA. In 2011 Fornasier was appointed Chair of Applied Numerical Analysis at TUM. He is a member of VQR, a panel responsible for the evaluation of the quality of research in Italy. He is also a member of the editorial boards of Networks and Heterogeneous Media, Journal of Fourier Analysis and Applications and Calcolo.
- Starting Grant from the European Research Council (2012)
- Biennal Prize of the Società Italiana di Matematica Applicata ed Industriale (SIMAI), first edition (2012)
- START award of the Austrian Science Fund (FWF) (2011)
- Best Paper Award of the Austrian Academy of Sciences (2010)
- Prix de Boelpaepe for image processing of the Royal Academy of Belgium (2009)
Caponigro M, Fornasier M, Piccoli B, Trélat E: “Sparse stabilization and control of alignment models Math”. Models Methods Appl. Sci. 2015; 25(3): 521-564.
Solombrino F, Fornasier M: “Mean-field optimal control.” ESAIM: Control, Optimization, and Calculus of Variations. 2014; 20(4): 1123-1152.
Carrillo JA, Fornasier M, Rosado J, Toscani G: “Asymptotic flocking dynamics for the kinetic Cucker-Smale model”. SIAM. J. Math. Anal. 2010; 42(1): 218-236.
Daubechies I, DeVore R, Fornasier M, Güntürk CS: “Iteratively re-weighted least squares minimization for sparse recovery Commun”. Pure Appl. Math. 2010; 63(1): 1-38.
Rauhut H, Fornasier M: “Recovery algorithms for vector valued data with joint sparsity constraints”. SIAM J. Numer. Anal. 2008; 46(2): 577-613.