Sara Garbarino


IRCCS Ospedale Policlinico San Martino, Genova
Life Science Computational (LISCOMP) laboratory
and Methods for Image and Data Analysis (MIDA) group
Università di Genova

Curriculum (at a glance)

Previous positions

Postdoctoral research fellow (2020-2022): Inversion methods with applications to Fourier-type data, MIDA group, UNIGE Research fellow of the Université Côte d'Azur Excellence Program (2018-2020) with the project: A data-driven model of mechanistic brain Atrophy Propagation in Dementia, Epione team, INRIA
Research associate (2016-2018): Computational modelling of neurological disease progression, POND group, CMIC, UCL
Postdoctoral research fellow (2015-2016): Inversion methods with applications to biomedical data, MIDA group, UNIGE


PhD in Mathematics and Applications (2015) : Compartmental analysis in nuclear medicine: an inverse problem approach, MIDA group, UNIGE
MSc magna cum laude in Applied Mathematics (2011): UNIGE
BSc in Pure Mathematics (2009) : UNIGE

See my complete CV

Publications (main)

2022 Massa P, Garbarino S, Benvenuto F
Approximation of discontinuous inverse operators with neural networks
Inverse Problems 38(105001)

2022 Grisanti S, Garbarino S, Barisione E, Aloe T, Grosso M, et al
Neurological long-COVID in the outpatient clinic: Two subtypes, two courses
Journal of the Neurological Sciences 52(1)

2021 Wijeratne PA, Garbarino S, Gregory S, Johnson EB, Scahill RI, Paulsen JS, Tabrizi SJ, Lorenzi M, Alexander DC
Revealing the timeline of structural MRI changes in premanifest to manifest Huntington disease
Neurology Genetics 7(5)

2021 Garbarino S and Lorenzi M
Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain
Neuroimage 235, 117980

2021 Bellio M, Furniss D, Oxtoby NP, Garbarino S, Firth N, RIbbens A, Alexander DC, Blanford A
Opportunities and barriers for adoption of a decision--support tool for Alzheimer's Disease
ACM Transactions on Computing for Healthcare, in press

2020 Pascuzzo R, Oxtoby NP, Young A, Blevins J, Castelli G, Garbarino S, Cohen M, Schonberger L, Gambetti P, Appleby B, Alexander DC, Bizzi A
Prion propagation estimated from brain diffusion MRI is subtype dependent in sporadic Creutzfeldt–Jakob disease
Acta Neuropathologica 140, 169--181

2019 Garbarino S, Lorenzi M, Oxtoby N, Vinke E, Marinescu R, Eshaghi A, Ikram M, Niessen W, Ciccarelli O, Barkhof F, Schott J, Vernooij M, Alexander D
Differences in topological progression profile among neurodegenerative diseases from imaging data
eLife 2019(8), e49298

2019 Garbarino S and Lorenzi M
Modeling and inference of spatio-temporal protein dynamics across brain networks
Lecture Notes in Computer Science 11492, 37--69

2019 Garbarino S and Caviglia G
Multivariate Regularized Newton and Levenberg-Marquardt methods: a comparison on synthetic data of tumor hypoxia in a kinetic framework
Communications in Applied and Industrial Mathematics 10(2) 47--53

2019 Marinescu R, Eshaghi A, Lorenzi M, Young A, Oxtoby N, Garbarino S, Crutch S, Alexander A
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders
Neuroimage 162 166--177

2018 Delbary F and Garbarino S
Compartmental analysis of dynamic nuclear medicine data: regularization procedure and application to physiology
Inverse Problems in Science and Engineering 1--19

2018 Scussolini M, Garbarino S, Piana M, Sambuceti G and Caviglia G
Reference Tissue Models for FDG-PET Data: Identifiability and Solvability
IEEE Trans. Rad. Plasma Med. Sciences 99

2017 Scussolini M, Garbarino S, Sambuceti S, Caviglia G and Piana M
A physiology--based parametric imaging method for FDG--PET data
Inverse Problems 33 125010

2017 Oxtoby N, Garbarino S, Firth N, Warren J, Schott M, Alexander D and ADNI
Data driven model of structural brain connectivity changes in sporadic Alzheimer's Disease
Frontiers in Neurology 8 580

2017 Denevi G, Garbarino S and Sorrentino A
Iterative algorithms for a non--linear inverse problem in atmospheric lidar
Inverse Problems 33 085010

2016 Delbary F, Garbarino S and Vivaldi V
Compartmental analysis of dynamic nuclear medicine data: models and identifiability
Inverse Problems 32 125010

2016 Garbarino S, Sorrentino A, Massone AM., Sannino A, Biselli A, Wuang X, Spinelli N and Piana M
Expectation Maximization and the retrieval of the atmospheric extinction coefficients by inversion of Raman LIDAR data
Optics Express 24(19) 21497--21511

2015 Garbarino S, Vivaldi V, Delbary F, Caviglia G, Piana M, Marini C, Capitanio S, Calamia I, Buschiazzo A and Sambuceti G
A new compartmental method for the analysis of liver FDG kinetics in small animal models
European Journal of Nuclear Medicine and Molecular Imaging Research, 2015, 5-35

2014 Garbarino S, Caviglia G, Sambuceti G, Benvenuto F and Piana M
A novel description of FDG excretion in the renal system: application to metformin-treated models
Physics in Medicine and Biology, 59, 2469-2484

2013 Garbarino S, Caviglia G, Brignone M, Massollo M, Sambuceti G and Piana M
Estimate of FDG excretion by means of compartmental analysis and Ant Colony Optimization of nuclear medicine data
Computational and Mathematical Methods in Medicine, 2013, 793142, 10 pages

Ongoing Projects

Progetto di rete (funded by the italian ministry of health): "NeuroartP3 - Artificial intelligence of imaging and clinical neurological data for predictive, preventive and personalized medicine", PI Antonio Uccelli

5X1000 IRCCS Ospedale Policlinico San Martino: "Parametric imaging in oncology", PI Cristina Campi