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Curriculum vitae
Germana Landi
23 dicembre 2014
Affiliation
Department of Mathematics, Bologna University,
Piazza di Porta San Donato, 5, 40127 Bologna, Italy
Phone: +39 051 2094480
Fax: +39 051 2094490
E-mail: [email protected]
http://www.dm.unibo.it/ landig/
Personal Data
Germana Landi
Born in Bologna, Italy, on June 25, 1973
Italian nationality
Education
Ph. D. in Computational Mathematics, Padova University, Italy
Date of defence: February 8, 2001
Thesis title: Metodi numerici per la minimizzazione di funzioni (Numerical methods for functions minimization)
Supervisor: Prof. I. Galligani
Laurea (cum laude) in Mathematics, Bologna University, Italy
Date of defence: February 21, 1997
Thesis title: Soluzione numerica ai problemi di controllo ottimo (Numerical solution to optimal control problems)
Supervisor: Prof. I. Galligani
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Professional Experience
December 2008 - present
Permanent position of Researcher of Numerical Analysis, Bologna University, Italy
October 2006 - October 2008
Postdoctoral fellow at the Mathematics Department of the Bologna University
July 2006 - September 2006
Postdoctoral fellow (called contratto di collaborazione alla ricerca) at the
Mathematics Department of the Bologna University
June 2001 - June 2006
Postdoctoral fellow (called assegno di ricerca) at the Mathematics Department of the Bologna University
Research Fields
• Nonlinear optimization methods
• Optimization techniques for regularized inverse problems and sparse recovery
• Inverse problems in imaging: image restoration, denoising and deblurring
• Medical and astronomical imaging
Software Package
• MRITool, a Matlab package with graphical interface for the reconstruction
of dynamic Magnetic Resonance Images.
• NPTool, a software package for image denoising and deblurrig from Gaussian or Poisson corrupted data.
Collaborations in Research Projects
• Studio di Fattibilità FARB 2013(Università degli Studi di Bologna): “Metodi numerici di regolarizzazione per l’inversione di dati in Fisica Applicata”; coordinatore: prof. Nico Lanconelli; duration: 24 months.
• GNCS 2014: “Metodi di ottimizzazione del primo ordine per l’elaborazione
e l’analisi di immagini”; PI: prof. Daniela di Serafino; duration: 12 month.
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• GNCS 2013: “Metodi numerici e software per l’ottimizzazione su larga
scala con applicazioni all’image processing”; PI: prof. Daniela di Serafino;
duration: 12 month.
• PRIN2008 “Optimization Methods and Software for Inverse Problems”;
PI: prof. Valeria; duration: 24 months; prot. N. 2008T5KA4L.
• PRIN2006 “Inverse Problems in Medicine and Astronomy”; PI: prof. Mario Bertero; duration: 24 months; prot. N. 2006018748.
• PRIN2004 “Inverse Problems in Medical Imaging”; PI: prof. Andreas
Formiconi; duration: 24 months; prot. N. 2004015818.
• Cofin2002 “Inverse Problems in Medical Imaging”; PI: prof. Mario Bertero; duration: 24 months; prot. N. 2002013422.
• Firb 2001 “Parallel Algorithms and Numerical Nonlinear Optimization”;
role: participant; PI: prof. Valeria Ruggiero; duration: 36 months; grant
n. RBAU01JYPN.
Complete List of Publications
Refereed Journal Publications
• G. Landi. A Modified Newton Projection Method for L1-Regularized
Least Squares Image Deblurring, Journal of Mathematical Imaging
and Vision, DOI: 10.1007/s10851-014-0514-3, 2014.
• G. Landi and E. Loli Piccolomini. NPTool: a Matlab software
for nonnegative image restoration with Newton projection methods.
Numerical Algorithms, Vol. 62 (3), pp. 487-504, 2013.
• S. Bonettini, G. Landi, E. Loli Piccolomini and L. Zanni. Scaling
techniques for gradient projection-type methods in astronomical image deblurring, International Journal of Computer Mathematics, Vol.
90 (1), pp. 9-29, 2013.
• G. Landi and E. Loli Piccolomini. A feasible direction method for
image restoration. Optimization Letters, vol. 6 (8), pp. 1795-1817,
2012.
• G. Landi and E. Loli Piccolomini. An improved Newton projection
method for nonnegative deblurring of Poisson-corrupted images with
Tikhonov regularization. Numerical Algorithms, Vol. 60(1), pp. 169188, 2012.
• G. Landi and E. Loli Piccolomini. An efficient method for nonnegatively constrained Total Variation-based denoising of medical images corrupted by Poisson noise. Computerized Medical Imaging and
Graphics, Vol.36(1), pp. 38-46, 2012.
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• G. Landi and E. Loli Piccolomini. Quasi-Newton projection methods and the discrepancy principle in image restoration. Applied
Mathematics and Computation, Vol. 218, pp. 2091-2107, 2011.
• G. Landi and E. Loli Piccolomini. An iterative Lagrange method for
the regularization of discrete ill-posed inverse problems. Computers
and Mathematics with Applications, Vol. 60, pp. 1723-1738, 2010.
• G. Landi and E. Loli Piccolomini. An algorithm for image denoising
with automatic noise estimate. Journal of Mathematical Imaging and
Vision, Vol. 34(1), pp. 98-106, 2009.
• G. Landi, E Loli Piccolomini and F. Zama. A Total Variationbased re- construction method for dynamic MRI. Computational and
Mathematical Methods in Medicine, Vol. 9, pp. 69 - 80, 2008.
• G. Landi and E. Loli Piccolomini. A projected Newton-CG method
for nonnegative astronomical image deblurring. Numerical Algorithms, Vol. 48, pp. 279-300, 2008.
• G. Landi and E. Loli Piccolomini. A fast projected quasi-Newton method for nonnegative Tikhonov regularization. International Journal
of Mathematics and Computer Science, Vol. 3(3), pp. 199-213, 2008.
• G. Landi. The Lagrange method for the regularization of discrete
ill-posed problems. Computational Optimization and Applications,
Vol. 39, pp.347-368, 2008.
• G. Landi, E. Loli Piccolomini, and F. Zama. A Total Variationbased reconstruction method for dynamic MRI. Computational and
Mathematical Methods in Medicine, 9(1), pp.69-80, 2008.
• G. Landi. A Truncated Lagrange Method for Total Variation-based
Image Restoration. Journal of Mathematical Imaging and Vision,
Vol. 28(2), pp. 113-123, 2007.
• G. Landi and E. Loli Piccolomini. Numerical methods for the reconstruction of dynamic Magnetic Resonance Images. Inverse Problems
in Science and Engineering, Vol. 15(3), 2007.
• G. Landi, and E. Loli Piccolomini. Fast methods for MR spectroscopic imaging. Applied Mathematics and Computation, Vol. 191(2),
pp. 389-396, 2007.
• G. Landi. A Fast Truncated Lagrange Method for Large-Scale Image
Restoration Problems. Applied Mathematics and Computation, Vol.
186(2), pp. 1075-1082, 2007.
• G. Landi. Total variation minimization subject to a noise constraint.
International Journal of Mathematics and Computer Science, Vol. 2,
pp. 95-115, 2007.
• G. Landi, and E. Loli Piccolomini. Representation of high resolution
images from low sampled Fourier data. Journal of Mathematical
Imaging and Vision, Vol. 26(1-2), pp. 27-40, 2006.
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• G. Landi, and F. Zama. The active-set method for nonnegative regularization of linear ill-posed problems. Applied Mathematics and
Computation, Vol. 175(1), pp. 715-729, 2006.
• G. Landi, and E. Loli Piccolomini. A Total Variation regularization
strategy in dynamic MRI. Optimization Methods and Software, Vol.
20(4-5), pp. 545-558, 2005.
• E. Loli Piccolomini, G. Landi, and F. Zama. A B-spline parametric model for high resolution dynamic Magnetic Resonance Imaging.
Applied Mathematics and Computation, Vol. 164, pp. 133-148, 2005.
• D. Calvetti, G. Landi, L. Reichel, and F. Sgallari. Nonnegativity and
iterative methods for ill-posed problems. Inverse Problems, Vol. 20,
pp. 1747-1758, 2004.
Publications in peer-reviewed Conference Proceedings
• G. Landi, A Lagrange method based L-curve for image restoration,
Journal of Physics: Conference Series Volume 464, Issue 1, 2013,
Article number 012011, NCMIP 2013.
• G. Landi, E. Loli Piccolomini and F. Zama. Regularization Methods
for Discrete Ill-posed Problems in Imaging. A cura di D. Bainov. International Journal of Pure and Applied mathematics. Fifth International Conference of Applied Mathematics and Computing. Plovdiv,
Bulgaria. August 12-18, 2008. vol. 49, pp. 413-420, 2008.
• G. Landi, E. Loli Piccolomini, and F. Zama, A Total Variation-based
regularization strategy in Magnetic Resonance Imaging. Image Reconstruction from Incomplete Data III, Philip J. Bones, Michael A.
Fiddy, Rick P. Millane Editors, Proceedings of SPIE, Vol. 5562, pp.
141-151, 2004.
• F. Zama, E. Loli Piccolomini, and G. Landi. A descent method
for linear inverse problems. Image Reconstruction from Incomplete
Data III, Philip J. Bones, Michael A. Fiddy, Rick P. Millane Editors,
Proceedings of SPIE, Vol. 5562, pp. 152-160, 2004.
• G. Landi, E. Loli Piccolomini, and F. Zama. A Parallel Software for
the Reconstruction of Dynamic MRI Sequences. Proceedings of 10th
European meeting PVM/MPI, LNCS 2840 (Springer), pp. 511-5196,
2003.
Reports, papers submitted and in preparation
• R. De Asmundis, D. di Serafino, G. Landi, On the regularizing behavior of recent gradient methods in the solution of linear ill-posed
problems, 2014 (available from Optimization Online)
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• G. Landi. A discrete L-curve for the regularization of ill-posed inverse
problems. Optimization Online
• G. Landi. Lagrangian methods for the regularization of discrete illposed problems. Memorie dell’Accademia delle Scienze dell’Istituto
di Bologna, Serie I, 2005, Bologna, Italia.
• G. Landi and E. Loli Piccolomini. Numerical methods for dynamic
Magnetic Resonance Imaging. Memorie dell’Accademia delle Scienze
dell’Istituto di Bologna, Serie I, 2005, Bologna, Italia.
• E. Loli Piccolomini, G. Landi, F. Zama. A B-spline parametric model
for high resolution dynamic Magnetic Resonance Imaging. Trattamento Numerico delle immagini e applicazioni alla medicina, a cura
di E. L. Piccolomini, Atti dell’Accademia delle Scienze dell’Istituto
di Bologna, Serie I, Vol. II, pp. 3-18, 2004.
• G. Landi, and F. Lasagni. MRITool: a Software for the Reconstruction of MRI Sequences. Trattamento Numerico delle immagini
e applicazioni alla medicina, a cura di E. L. Piccolomini, Atti dell’Accademia delle Scienze dell’Istituto di Bologna, Serie I, Vol. II,
pp. 19-29, 2004.
• G. Landi. Metodi Numerici per la Minimizzazione di Funzioni. Tesi
di Dottorato in Matemtatica Computazionale, Università di Padova,
2001.
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