CV Lattes
Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC) (Institutional affiliation from the last research proposal) Birthplace: Argentina
Graduated in Mathematics at the University of Buenos Aires (1973), PHd in Applied Mathematics from the Federal University of Rio de Janeiro (1981). Since 1996, Professor of Applied Mathematics at the University of Campinas. He held research and visiting positions at the Institute for Pure and APplied Mathematics (IMPA-RJ, 1985), the University of Pennsylvania (1986-87, Department of Radiology) and the University of California, Los Angeles (2000-01, Department of Mathematics). His main research areas are: inverse problems, image processing and reconstruction, tomography (transmission and emission), linear algebra, computational Fourier Analysis and signal processing. (Source: Lattes Curriculum)
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Tomographic reconstruction created a major impact in Medicine. It has allowed non invasive visualization of anatomic structures, metabolism and function of human body. Over the last 30 years, the progresses on tomographic reconstruction techniques have been enormous, both in terms of quality and performance, as well as on dynamic and tridimensional techniques [Udupa, 2000]. However, there…
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Many Inverse Problems, especially in emission and X rays computed tomography, are modeled by large scale systems of linear equations that give rise to ill conditioned mathematical problems. In order to find a stable solution it is necessary to add information not contained in the equations. All this information is used through different models where either an optimization or a feasibility…
In our Doctoral Thesis we built an analytic formula for the inversion of the Generalized Radon Transform corresponding to the fluorescence tomography problem as well as several iterative methods. In this project we propose to continue our previous work improving the implementation of our analytic formula, analysing the possibility of its extension to three dimensions and the possible cons…
In our doctoral dissertation we presented a general framework that includes many known as well as new methods for solving convex feasibility problems and for constrained nondifferentiable optimization. These methods generalize orthogonal projection methods for convex feasibility as well as underrelaxed methods for nondifferentiable convex optimization. This project aims at extending these…
(Only some records are available in English at this moment)
| 9 / 6 | Completed research grants |
| 12 / 5 | Completed scholarships in Brazil |
| 21 / 11 | All research grants and scholarships |
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