This curriculum vitae summarizes Nicola Amoroso's education and professional experience. He holds a PhD in Physics from 2014 with a thesis on quantitative MRI analysis in Alzheimer's disease. His postdoctoral research has focused on developing cloud computing solutions to support neuroimaging data analysis. He has published over 10 papers in peer-reviewed journals on topics including hippocampal segmentation, machine learning applications for brain disease detection, and complex network analysis of neuroimaging data.

1. Curriculum Vitae et studiorum
Nicola Amoroso
address: Via dell'ecologia 8, 76011, Bisceglie (BT), Italy
cell: +39 331 5856943
tel: +39 080 3958683
email: nicola.amoroso@ba.infn.it
skype contact: nic.amoroso
Birth date: 04 Maggio 1980
Instruction
26/05/2014 PhD in Physics with the thesis Quantitative MRI analysis in Alzheimer's Disease
21/07/2010 M.Sc. (Physics) 110/110 cum laude with the thesis An econophysics approach for
the determination of the regulatory capital for the operative risk.
Academic Experience
17/06/2016 – ongoing Post-doc position for the Study, development and test of complex
network solutions according to the cloud computing paradigm to support neuroimaging data
analyses.
16/06/2015 – 16/06/2016 Post-doc position for the Study, development and test of complex
network solutions according to the cloud computing paradigm to support neuroimaging data
analyses.
17/03/2014 – 17/03/2015 Post-doc position for the Study, development and test of computing
solutions and data storage according to the cloud computing paradigm to support biomedical data
analyses.
Didactics experiences
2014 – 2015 Professor for the course General Physics II (Electromagnetic interactions of current
and charges) at (DICATECH) – Politecnico degli studi di Bari, Bari (Italy)

2. 2014 Professor of Medical Physics at the IV Egyptian High Energy Physics School at the Ain
Shams University and The British University in Egypt, Cairo (Egypt)
2010 - 2013 Teaching assistant of General Physics I (Mechanics and Thermodynamics) at the
faculty of Pharmacy – Università degli studi di Bari, Bari (Italy).
2003 - 2010 External expert in high-school courses funded by EU National Operative
Programme.
Research experiences
The two main fields of my research experience concern:
1. Neuroimaging: MRI, DWI analyses, image processing and machine learning
applications for pattern recognition
2. Biomedical Data analysis: data mining, statistics, imaging genetics, co-expression
networks, GWAS.
In more details I have gained research experience in the following fields:
Blind validation of predictive algorithms for brain diseases
The international research community has devoted a huge effort to the development and
sharing of robust methodologies for quantitative assessment of brain diseases. In
particular, the lack of an unbiased comparison among different studies and methodology
affects the replicability of results and therefore weakens their scientific contribution.
Accordingly, in recent years a number of international challenges have been promoted to
compare algorithms and methodologies within a common framework. The algorithms
designed and implemented by me, with the invaluable support of all the research team,
reached considerable results and were published on high impact international journals
[P1, P9, C7, C8]1.
Neurodegenerative diseases, design and implementation of quantitative methods for the assessment
and the support to diagnosis
During my PhD and the following years as a post-doc I have been involved in two Italian
collaborations focused on the study of neurodegenerative diseases, specifically
Alzheimer’s disease. Firstly, I developed novel segmentation algorithms for the
hippocampal segmentation and therefore the evaluation of its atrophy rate [P8, P10-P11,
C3-C14]. I adopted machine learning strategies especially based on Random Forests,
Support Vector Machines and Artificial Neural Networks to develop quantitative indexes
to support the diagnosis [P2-P6, P12]. This kind of analysis often require big data
strategies and computational facilities; however, I have always designed my pipelines to
exploit parallel or distributed computations. With this regard, I managed to exploit the
5000 CPUs available in Bari with its RECAS computer cluster. Currently, I am
1 P: regular article publication , C: conference proceeding

3. investigating other unsupervised learning strategies, especially deep learning based to
exploit these huge computational resources. Moreover, I was inspired by recent works on
brain connectivity adopting complex networks. This is why in the last year my research
was almost completely devoted to investigate the applications of complex network
methodologies [P7, C1, C2].
Quantitative methodologies for socio-economic applications
Beyond my research activities (including 26 publications to date, 12 research paper and 14
proceedings) I enthusiastically get involved in research projects related to other fields. In
particular, I collaborated with the United Nations (UN) Department of Economic and
Social Affairs (DESA) for the development and statistical assessment of the e-Government
Development Index (EGDI), a collaboration acknowledged by the UN EGDI Survey 2012
and 2014.
In the following a brief summary of the methodologies and techniques I get used with
during my research activity:
 Image Pre-processing: registration for 2D and 3D medical images, wavelet
denoising, Fourier analyses, image enhancement.
 Shape Analysis: SPHARM methodologies, Point Distribution Model, applications to
structural MRI.
 Hippocampal Segmentation: Pattern recognition, statistical approaches, machine
learning.
 Quantitative biomarkers: multivariate analyses, classification indexes and similarity
patterns.
 Machine learning for the classification of neurodegnerative diseases. Design and
development of algorithms (see for example international challenge “CAD
dementia” and “Machine Learning” MICCAI 2014).
 Design and development of workflows within the Software as a Service paradigm.
 MRI structural connectivity: graph theory, complex networks and multi-graphs for
the characterization of brain diseases.
 Data mining: data pre-processing (data cleaning, missing data, data
transformation), explorative analysis, multivariate data characterization.
 Unsupervised analysis: data reduction (Non negative matrix factorization, Principal
component analysis (PCA), single value decomposition (SVD), factor analysis and
linear discriminant analysis (LDA)), clustering (K-means, linkage).
 Data modeling: Complex networks, applications to social-economic systems (e.g.
rating), imaging (segmentation and classification) e medical imaging (graph cuts).
 Machine learning: Classification and regression (Random Forests, Support Vector
Machines, Artificial Neural Networks, RUSBoost, Logistic regressions).
 Statistical evaluations: hypothesis tests (t-test, Kolmogorov-Smirnov, Wilcoxon,
Fisher, ...)
IT skills

4. All the analyses conducted both during the master degree and the PhD involved the
intensive use of MATLAB, I acquired about 10'000 hours of activity according to which I
can define myself a MATLAB expert. In the last two years I dedicated myself to the use of
R. Besides, I also experienced the use of Mathematica and Python. For imaging analyses, I
mainly used FSL, however I can also use FreeSurfer, SPM, ITK and openCV, the latter
being substantially C++ based. Moreover, I conducted several complex network analyses
with Gephi and NetLogo, even if the tool I adopted the most was the “igraph” R-package.
Finally, I have a solid experience with scripting (Bash) for the exploitation of distributed
infrastructures.

5. Publications
Publications in peer-reviewed international journals (impact factor at acceptance date)
1. Allen G I, AMOROSO N, et al., Crowdsourced estimation of cognitive decline and
resilience in Alzheimer's disease, ALZHEIMER’S & DEMENTIA 12.6 (2016): 645-653 IF
12.407
2. *Pergola G, Trizio S, Di Carlo P, Taurisano P, Mancini M, AMOROSO N, Nettis M
A, Andriola I, Caforio G, Popolizio T, Rampino A, Di Giorgio A, Bertolino A, Blasi
G, Grey Matter Volume Patterns in Thalamic Nuclei are Associated with Familial Risk for
Schizophrenia and with Schizotypy in healthy subjects, SCHIZOPHRENIA RESEARCH
doi:10.1016/j.schres.2016.07.005 IF 3.923
3. Tangaro S, Fanizzi A, AMOROSO N**, Corciulo R, Garuccio E, Gesualdo L, Loizzo
G, Procaccini D A, Vernò L, Bellotti R, Computer Aided Detection System for prediction
of the malaise during hemodialysis, COMPUTATIONAL AND MATHEMATICAL
METHODS IN MEDICINE http:dx.doi.org/10.1155/2016/8748156 (2916) IF 0.887
4. *Chincarini A, Sensi F, Rei L, Gemme G, Squarcia S, Longo R, Brun F, Tangaro S,
Bellotti R, AMOROSO N, Bocchetta M, Redolfi A, Bosco P, Boccardi M, Frisoni G B,
Nobili F, Integrating longitudinal information in hippocampal volume measurements for
the early detection of Alzheimer’s disease, NEUROIMAGE 125: 834-847 (2016) IF 6.357
5. AMOROSO N, Errico R, Bruno S, Chincarini A, Garuccio E, Sensi F, Tangaro S,
Tateo A, Bellotti R, Hippocampal Unified Multi-Atlas Network (HUMAN): protocol and
scale validation of a novel segmentation tool, PHYSICS IN MEDICINE AND BIOLOGY
60.22: 8851 (2015) IF 2.761
6. Inglese P, AMOROSO N, Boccardi M, Bocchetta M, Bruno S, Chincarini A, Errico R,
Frisoni G B, Maglietta R, Redolfi A, Sensi F, Tangaro S, Tateo A Bellotti R, Multiple
RF Classifier for the hippocampus segmentation: method and validation on EADC-ADNI
Harmonized Hippocampal Protocol, PHYSICA MEDICA 31.8: 1085-1091 (2015) IF 2.403
7. Nicotri S, Tinelli E, AMOROSO N, Garuccio E, Bellotti R, Complex networks and
public funding: the case of 2007-2013 Italian program, EPJ DATA SCIENCE 4.1: 1-19
(2015) IF under evaluation
8. Maglietta R AMOROSO N, Boccardi M, Bruno S, Chincarini A, Frisoni G B, Inglese
P, Redolfi A, Tangaro S, Tateo A, Bellotti R, Automated hippocampal segmentation in
3D MRI using random undersampling with boosting algorithm, PATTERN ANALYSIS
and APPLICATIONS 1-13 (2015) IF 0.646
9. E E Bron, M Smits, W M van der Flier, H Vrenken, F Barkhof, P Scheltens, J M
Papma, R M Steketee, C M Orellana, R Meijboom, M Pinto, J R Meireles, C Garrett,
A J Bastos-Leite, A Abdulkadir, O Ronneberger, AMOROSO N, et al., Standardized
evaluation of algorithms for computer-aided diagnosis of dementia based on
structural MRI: the CADDementia challenge. NEUROIMAGE, 111 (2015): 562-579
IF 6.357
10. Tangaro S, AMOROSO N., Brescia M, Cavuoti S, Chincarini A, Errico R, Inglese P,
Longo G, Maglietta R, Tateo A, Riccio G, Bellotti R. Feature Selection based on
Machine Learning in MRIs for Hippocampal Segmentation. COMPUTATIONAL
AND MATHEMATICAL METHODS IN MEDICINE dx.doi.org
/10.1155/2015/814104 (2015) IF 0.887
11. Tangaro S, AMOROSO N**, Boccardi M, Bruno S, Chincarini A, Ferraro G, Frisoni
G B, Maglietta R, Redolfi A, Rei L, Tateo A, Bellotti R (2014). Automated voxel-by-

6. voxel tissue classification for hippocampal segmentation: Methods and Validation.
PHYSICA MEDICA, 30.8: 878-887 (2014) IF 2.403
12. *Chincarini A, Bosco P, Gemme G, Morbelli S, Arnaldi D, Sensi F, Solano I,
AMOROSO N., Tangaro S, Longo R, Squarcia S, Nobili F. Alzheimer’s disease
markers from structural MRI and FDG-PET brain images. THE EUROPEAN
PHYSICAL JOURNAL PLUS, ISSN: 2190-5444 (2013) IF 1.377
* Publication without the participation of PhD supervisor
** Corresponding author

7. Indexed conference proceedings, abstracts and Book chapters
1. Monda A, AMOROSO N**, Altomare Basile M T, Bellotti R, Bertolino A, Blasi G, Di
Carlo P, Fanizzi A, La Rocca M, Maggipinto T, Monaco A, Paplino M, Pergola G,
Tangaro S, A gene-oriented community detection strategy:the DRD2 case study, In NDES
2015: Nonlinear Dynamics of Electronic Systems (in press)
2. La Rocca M, AMOROSO N**, Bellotti R, Diacono D, Monaco A, Monda A, Tateo A,
Tangaro S, A multiplex network model to characterize brain atrophy in structural MRI, In
NDES 2015: Nonlinear Dynamics of Electronic Systems (in press)
3. AMOROSO N, Antonacci M, Bellotti R, Donvito G, Errico R, Maggi G, Monaco A,
Notarangelo P, Tangaro S, Tateo A, Medical Physics Applications in Bari ReCaS Farm
In High Performance Scientific Computing Using Distributed Infrastructures:
Results and scientific applications derived from the Italian PON ReCaS Project
(2016)
4. AMOROSO N, Tangaro S, Errico R, Garuccio E, Monda A, Sensi F, Tateo A, Bellotti
R, An Hippocampal Segmentation Tool Within an Open Cloud Infrastructure, In ICIAP
2015: New Trends in Image Analysis and Processing (2015)
5. AMOROSO N**, Errico R, Ferraro G, Tangaro S, Tateo A, Bellotti R (2014). Fully
automated MRI analysis for brain diseases with high performance computing. In:
SCORE@POLIBA (2014)
6. Tangaro S, AMOROSO N., Chincarini A, Errico R, Frisoni G B, Maglietta R, Tateo
A, Bellotti R (2014). A Novel Approach for Fully Automatic Segmentation of
Hippocampus in MRI: Methods and Validation. In: MILANO 2014 dagli atomi al
cervello (2014)
7. *Sensi F, Rei L, Gemme G, Bosco P, AMOROSO N., Chincarini A. GDI*, a novel tool
for MTL atrophy assessment. In: Proceedings of the Computer-Aided Diagnosis of
Dementia Based on Structural MRI Data, MICCAI 2014., p. 92-101 (2014)
8. AMOROSO N**, Errico R, Bellotti R. PRISMA-CAD: Fully automated method for
Computer-Aided Diagnosis of Dementia based on structural MRI data. In:
Proceedings of the Computer-Aided Diagnosis of Dementia Based on Structural
MRI Data, MICCAI 2014, p. 16-24 (2014)
9. Tangaro S, AMOROSO N, Maglietta R, Errico R, Monaco A, Tateo A, Bellotti R
(2013). A Grid-based MRI segmentation: a comparison between Random Forests
and Neural Networks. In: ISMRM 2014 (International Society for Magnetic
Resonance in Medicine) (2014)
10. *La Neve A, Boero G, Internò S, Pietrafusa N, AmorosoMG, Durante V, Luisi C,
AMOROSO N. Pragmatic long-term open-label study on the effectiveness of
Lacosamide as add-on therapy in refractory partial Eplieptic patients. EPILEPSIA,
ISSN: 1528-1167 (2014) IF 4.571
11. *Cardone C, Liguori G, Troiani T, Nappi A, AMOROSO N., Iaffaioli V R, Romano
C, Botti G, Vitagliano D, Martini G, Napolitano S, Morgillo F, Sforza V, Giunta E, Di
Maio M, De Vita F, Ciardiello F, Martinelli E Expression of AXL receptor and its
ligand GAS6 in colorectal cancer (CRC). ANNALS OF ONCOLOGY, ISSN: 0923-
7534 (2014) IF 7.040
12. Tangaro S, AMOROSO N., Bruno S, Chincarini A, Frisoni G B, Maglietta R, Tateo A,
Bellotti R. Active Learning Machines for Automatic Segmentation of Hippocampus
in MRI. In: ICDM2013 proceedings (2013)

8. 13. Maglietta R, AMOROSO N., Bruno S, Chincarini A, Frisoni G B, Inglese P, Tangaro
S, Tateo A, Bellotti R. Random forest classification for hippocampal segmentation in
3D MR images. In: ICMLA 2013 proceedings (2013)
14. AMOROSO N**, Bellotti R, Bruno S, Chincarini A, Logroscino G, Tangaro S, Tateo
A. Automated Shape Analysis landmarks detection for medical image processing.
In: Proceedings of the International Symposium, CompIMAGE (2012)
Bari, 29/08/2016
Nicola Amoroso

9. Referees (contact details)
1) Prof. Roberto Bellotti, (PhD supervisor)
Affiliations: Bari University, Physics Department (UNIBA)
email: roberto.bellotti@uniba.it
2) Dr. Sabina Tangaro, (Collaboration)
National Institute of Nuclear Physics (INFN - Bari)
email: sonia.tangaro@ba.infn.it
3) Dr. Andrea Chincarini, (Collaboration)
Affiliations: National Institute of Nuclear Physics (INFN - Genova)
email: andrea.chincarini@ge.infn.it
Bari, 28/07/2016
Nicola Amoroso