Stefano Ferrari’s
Curriculum Vitæ et Studiorum
April 2014
Office:
Università degli Studi di Milano
Department of Computer Science
via Bramante 65, 26013 Crema (CR)
tel 02 503 300 62
fax 02 503 300 10
e-mail [email protected]
web http:://homes.di.unimi.it/ferrari
Short biography
Stefano Ferrari was born in Milano, Italy on February 4 1968.
Education
1995 Laurea degree in Computer Science (109/110), Università degli Studi di Milano.
2001 Ph.D. in Computer and Automation Engineering, Politecnico di Milano.
Positions
1996–1998 Collaboration with:
• the Laboratory of Human Motion Analysis & Virtual Reality, Istituto di Neuroscienze e Bioimmagini, Italian National Research Council,
• the Department of Bioengineering of Politecnico di Milano.
2001–2002 Research associate at the Department of Information Technology, Università
degli Studi di Milano.
2002– Assistant professor at the Department of Information Technology (since 2012
flowed into the Department of Computer Science), Università degli Studi di Milano.
Teaching
Research
The research activity tackled different areas of theory and application of the neural
networks. The following topics were addressed:
1 Multiscale paradigms for signal representation
The research has been carried out with reference to the multiresolution representation of signals. In particular, a self-organizing multiscale neural network model has
been developed and confronted to the wavelet decomposition paradigm. Moreover,
a Support Vector Machine multiscale schema for regression has been proposed.
Results have been published in [L1, R1, R2, R6, R7, R9, R10, R13, C14]. Preliminary
results have been published in [C9, C10, C15, C18, C21, C25, C27, C28].
2 Three-dimensional image processing
Reconstruction and representation of three-dimensional surfaces has been the main
applicative field of the soft-computing models studied. The focus has been the
problem of the reconstruction of surfaces from noisy samples. Two different neural
approaches and a model based on Support Vector Machine has been applied to this
problem.
Results have been published in [L1, CL1, R1, R2, R5, R6, R10, R12, C5, C14, C19,
T1]. Preliminary results have been published in [C9, C10, C15, C17, C18, C20, C21,
C24, C26, C27, C28, C29, C30, C32].
3 Signal processing
Also more general aspects of signal processing has been considered in the research
activity. Here, both neural model and traditional techniques have been applied.
Results have been published in [C1, C2, C3, C4, C6, C7, C8, R3, R4, C11, C12, R8,
C31]. Preliminary results have been published in [C13, C16].
4 Methodological aspects for composite systems specification and design
In this research field, the problem of the implementation of soft-computing paradigm
has been studied. The embedded systems design methodologies are based on the
algorithmic descrition of the functionalities that have to be realized. A description
of this kind, for soft-computing paradigm, is evident only after the configuration
of the model has been carried out. The research focused on the integration of a
learning-by-example methodology with the traditional methodology.
Results have been published in [R11, C22, C23, CL2].
Teaching
2003–2008 “Fondamenti di informatica per la sicurezza”, Bachelor Degree in “Sicurezza
dei sistemi e delle reti informatiche”, Facoltà di Scienze MM. FF. NN., Università
degli Studi di Milano.
2003–2008 teaching support to the “Architetture degli elaboratori”, Bachielor Degree in
“Informatica”, Facoltà di Scienze MM. FF. NN., Università degli Studi di Milano.
2
Editorial activity
2004 and 2006 “Informatica applicata ai processi biotecnologici”, Master Degree in “Biotecnologie per l’Industria e per l’Ambiente”, Facoltà di Scienze MM. FF. NN.,
Università degli Studi di Milano.
2005 “Analisi statistica dei dati”, Bachelor Degree in “Scienza della Produzione e Trasformazione del Latte”, Facoltà di Agraria, Università degli Studi di Milano.
2010–2011 “Elaborazione delle immagini I”, Master Degree in “Scienze e Tecnologie dell’Informazione”, Facoltà di Scienze MM. FF. NN., Università degli Studi di Milano.
2011– “Image processing”, Master Degree in Computer Science, Università degli Studi
di Milano.
Invited talks/Tutorials
2012 Keynote speech Computational Intelligence for Surface Modeling (F. Bellocchio, N.
A. Borghese, S. Ferrari, V. Piuri), ICNNAI 2012 (The 7th International Conference
on Neural Networks and Artificial Intelligence), 10–12 October 2012, Minsk.
2011 Keynote speech Hierarchical Neural-based Techniques for Regression (V. Piuri, F.
Bellocchio, S. Ferrari, N. A. Borghese), INISTA 2011 (International Symposium on
INnovations in Intelligent SysTems and Applications), 15–18 June 2011, Istanbul.
2009 Tutorial 3D Scanners: state of the art (V. Piuri, F. Bellocchio, S. Ferrari), I2MTC
2009 (International Instrumentation and Measurement Technology Conference), 5–7
May 2009, Singapore.
Editorial activity
2006 and 2007 Guest Editor of the Special Section on Virtual Environments, HumanComputer Interface and Measurement Systems, IEEE Transactions on Instrumentation and Measurement.
Reviewer for the following journals:
• IEEE Transaction on Neural Networks
• IEEE Transaction on Instrumentation and Measurements
• IEEE Signal Processing Letters
• Integrated Computer-Aided Engineering, pubblicato da IOS Press
• Journal of Systems Architecture, pubblicato da Elsevier Science
• Neural Computing & Applications
• Optics Express
3
Publications
Reviewer for the following conferences: IMTC (2005, 2006), VECIMS (2003, 2006),
CIMSA (2004, 2007), HAVE (2007), WCCI (2008), VIMS (2001, 2002), Computing Frontiers (2004),
Organization
In 2013–2014 he has been Chair of the IEEE Italy Section Systems Council Chapter,
Vice-Chair in 2010–2012, and Secretary in 2009–2010.
He served as General chair for VECIMS 2011 and 2012, EESMS 2012–2014; Technical
program co-chair for HAVE 2007 and for VECIMS 2009 and 2010, publication chair for
EESMS 2010 and 2011, and program committee member for the following conferences:
• VECIMS (2004, 2005, 2006, 2008), IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems;
• WCCI 2008, IEEE World Congress on Computational Intelligence;
• EESMS 2010 (2010 IEEE Workshop on Environmental, Energy, and Structural
Monitoring Systems).
Publications
Scientific works can classified as follows:
Category
Books
Book chapters
International journals
International congresses
Other publications
Dissertations
# works
1
2
13
31
2
1
Books
[L1] F. Bellocchio, N. A. Borghese, S. Ferrari, and V. Piuri, 3D Surface Reconstruction:
Multi-Scale Hierarchical Approaches. Springer-Verlag New York, LLC, 2012.
Book chapters
[CL1] F. Bellocchio and S. Ferrari, Depth Map and 3D Imaging Applications: Algorithms
and Technologies, ch. 3D Scanner, State of the Art, pp. 451–470. IGI Global, 2011.
4
Publications
[CL2] S. Ferrari and V. Piuri, Neural networks for Instrumentation, Measurements, and
Related Industrial Applications, NIMIA 2001, ch. Neural Networks in Intelligent
Sensors and Measurement Systems for Industrial Applications, pp. 19–42. IOS
Press, 2003.
International journals
[R1]
F. Bellocchio, S. Ferrari, V. Piuri, and N. A. Borghese, “Hierarchical approach
for multiscale Support Vector Regression,” IEEE Trans. on Neural Networks and
Learning Systems, vol. 23, pp. 1448–1460, Sept. 2012.
[R2]
S. Ferrari, F. Bellocchio, V. Piuri, and N. A. Borghese, “A hierarchical RBF online
learning algorithm for real-time 3-D scanner,” IEEE Trans. on Neural Networks,
vol. 21, pp. 275–285, Feb. 2010.
[R3]
M. Lazzaroni, S. Ferrari, L. Cristaldi, and M. Annoni, “Nozzle and workingcondition classifications for water jet systems,” IEEE Trans. on Instr. and Meas.,
vol. 58, pp. 1546–1554, May 2009.
[R4]
M. Annoni, L. Cristaldi, M. Lazzaroni, and S. Ferrari, “Nozzles classification in a
high-pressure water jet system,” IEEE Trans. on Instr. and Meas., vol. 58, pp. 3739–
3745, Oct. 2009.
[R5]
S. Ferrari, G. Ferrigno, V. Piuri, and N. A. Borghese, “Reducing and filtering
point clouds with enhanced vector quantization,” IEEE Trans. on Neural Networks,
vol. 18, pp. 161–177, Jan. 2007.
[R6]
S. Ferrari, I. Frosio, V. Piuri, and N. A. Borghese, “Automatic multiscale meshing
through HRBF networks,” IEEE Trans. on Instr. and Meas., vol. 54, pp. 1463–1470,
Aug. 2005.
[R7]
S. Ferrari, M. Maggioni, and N. A. Borghese, “Multi-scale approximation with hierarchical radial basis functions networks,” IEEE Trans. on Neural Networks, vol. 15,
pp. 178–188, Jan. 2004.
[R8]
D. Perani, F. Fazio, N. A. Borghese, M. Tettamanti, S. Ferrari, J. Decety, and M. C.
Gilardi, “Different brain correlates for watching real and virtual hand actions,”
NeuroImage, vol. 14, pp. 749–758, Sept. 2001.
[R9]
S. Ferrari, N. A. Borghese, and V. Piuri, “Multiscale models for data processing:
an experimental sensitivity analysis,” IEEE Trans. on Instr. and Meas., vol. 50,
pp. 995–1002, Aug. 2001.
[R10] N. A. Borghese and S. Ferrari, “A portable modular system for automatic acquisition
of 3-D objects,” IEEE Trans. on Instr. and Meas., vol. 49, pp. 1128–1136, Oct. 2000.
[R11] C. Alippi, S. Ferrari, V. Piuri, M. Sami, and F. Scotti, “New trends in intelligent
systems design for embedded and measurement applications,” IEEE Instr. & Meas.
Mag., vol. 2, pp. 36–44, June 1999.
5
Publications
[R12] N. A. Borghese, G. Ferrigno, G. Baroni, A. Pedotti, S. Ferrari, and R. Savaré,
“Autoscan: a flexible and portable 3D scanner,” IEEE Computer Graphics and
Applications, vol. 18, pp. 38–41, May 1998.
[R13] N. A. Borghese and S. Ferrari, “Hierarchical RBF networks and local parameter
estimate,” Neurocomputing, vol. 19, no. 1–3, pp. 259–283, 1998.
International congresses
[C1]
S. Ferrari and G. Pentchev, “An android-based platform for augmented-reality remote inspection systems prototyping,” in Environmental Energy and Structural
Monitoring Systems (EESMS), 2013 IEEE Workshop on, pp. 1–6, sep 2013.
[C2]
“A data approximation based approach to photovoltaic systems maintenance,” in
Environmental Energy and Structural Monitoring Systems (EESMS), 2013 IEEE
Workshop on, pp. 1–6, sep 2013.
[C3]
S. Ferrari, M. Lazzaroni, V. Piuri, L. Cristaldi, and M. Faifer, “Statistical models approach for solar radiation prediction,” in Instrumentation and Measurement
Technology Conference (I2MTC), 2013 IEEE International, pp. 1734–1739, May
2013.
[C4]
S. Ferrari, M. Lazzaroni, V. Piuri, A. Salman, L. Cristaldi, and M. Faifer, “Computational intelligence models for solar radiation prediction,” in Instrumentation and Measurement Technology Conference (I2MTC), 2013 IEEE International,
pp. 757–762, May 2013.
[C5]
F. Bellocchio, N. A. Borghese, S. Ferrari, and V. Piuri, “Computational intelligence for surface modeling,” in ICNNAI’2012, Proceedings of the 7th International
Conference on Neural Networks and Artificial Intelligence, pp. 11–16, Oct. 2012.
[C6]
S. Ferrari, A. Fina, M. Lazzaroni, V. Piuri, L. Cristaldi, M. Faifer, and T. Poli, “Illuminance prediction through statistical models,” in Environmental Energy
and Structural Monitoring Systems (EESMS), 2012 IEEE Workshop on, pp. 90–96,
Sept. 2012.
[C7]
S. Ferrari, M. Lazzaroni, V. Piuri, A. Salman, L. Cristaldi, M. Rossi, and T. Poli,
“Illuminance prediction through Extreme Learning Machines,” in Environmental
Energy and Structural Monitoring Systems (EESMS), 2012 IEEE Workshop on,
pp. 97–103, Sept. 2012.
[C8]
F. Bellocchio, S. Ferrari, M. Lazzaroni, L. Cristaldi, M. Rossi, T. Poli, and R. Paolini, “Illuminance prediction through SVM regression,” in Environmental Energy and
Structural Monitoring Systems (EESMS), 2011 IEEE Workshop on, pp. 1–5, Sept.
2011.
[C9]
S. Ferrari, F. Bellocchio, V. Piuri, and N. Borghese, “Multi-scale support vector
regression,” in Proceedings of IJCNN 2010 (IEEE International Joint Conference
on Neural Networks), pp. 1–7, July 2010. Runner-up Best Paper.
6
Publications
[C10] F. Bellocchio, N. Borghese, S. Ferrari, and V. Piuri, “Kernel regression in HRBF networks for surface reconstruction,” in Proceedings of HAVE 2008 (IEEE International Workshop on Haptic Audio and Visual Environments and Games), pp. 160–165,
Oct. 2008.
[C11] S. Ferrari, V. Piuri, and F. Scotti, “Image processing for granulometry analysis via
neural networks,” in Proceedings of CIMSA 2008 (IEEE Conference on Computational Intelligence for Measurement Systems and Applications), pp. 28–32, July
2008.
[C12] S. Ferrari, V. Piuri, and F. Scotti, “Virtual environment for granulometry analysis,” in Proceedings of VECIMS 2008 (IEEE Conference on Virtual Environments,
Human-Computer Interfaces and Measurement Systems), pp. 156–161, July 2008.
[C13] M. Lazzaroni, S. Ferrari, M. Annoni, and L. Cristaldi, “A tool for working condition
and nozzles classification for water jet systems,” in Proceedings of IMTC 2008 (IEEE
Instrumentation and Measurement Technology Conference), pp. 1435–1440, May
2008.
[C14] S. Ferrari, F. Bellocchio, N. Borghese, and V. Piuri, “Refining hierarchical radial
basis function networks,” in Proceedings of HAVE 2007 (IEEE International Workshop on Haptic Audio and Visual Environments and Games), pp. 166–170, Oct.
2007.
[C15] F. Bellocchio, S. Ferrari, V. Piuri, and N. Borghese, “Online training of hierarchical
RBF,” in Proceedings of IJCNN 2007 (IEEE International Joint Conference on
Neural Networks), pp. 2159–2164, Aug. 2007.
[C16] M. Annoni, L. Cristaldi, M. Lazzaroni, and S. Ferrari, “Nozzles classification
in a high pressure water jet systems,” in Proceedings of IMTC 2007 (IEEE
Instrumentation and Measurement Technology Conference), pp. 1–6, May 2007.
[C17] S. Ferrari, I. Frosio, V. Piuri, and N. Borghese, “Enhanced vector quantization for
data reduction and filtering,” in Proceedings of 3DPVT 2004 (2nd International
Symposium on 3D Data Processing, Visualization and Transmission), pp. 470–477,
Sept. 2004.
[C18] S. Ferrari, I. Frosio, V. Piuri, and N. Borghese, “The accuracy of the HRBF
networks,” in Proceedings of IMTC 2004 (21th IEEE Instrumentation and
Measurement Technology Conference), pp. 482–486, May 2004.
[C19] N. Borghese, S. Ferrari, and V. Piuri, “A methodology for surface reconstruction
based on hierarchical models,” in Proceedings of HAVE 2003 (IEEE International
Workshop on Haptic Virtual Environments and Their Applications), pp. 119–124,
Sept. 2003.
[C20] N. Borghese, S. Ferrari, and V. Piuri, “Real-time surface meshing through HRBF
networks,” in Proceedings of IJCNN 2003 (IEEE-INNS-ENNS International Joint
Conference of Neural Networks), vol. 2, pp. 1361–1366, July 2003.
[C21] N. Borghese, S. Ferrari, and V. Piuri, “Real-time surface reconstruction through
HRBF networks,” in Proceedings of HAVE 2002 (IEEE International Workshop on
Haptic Virtual Environments and Their Applications), pp. 19–24, Nov. 2002.
7
Publications
[C22] S. Ferrari, M. Sami, and V. Piuri, “Paradigm-independent design of composite systems,” in Proceedings of CSCC 2001 — Advances in System Science: Measurement,
Circuits, and Control (N. Mastorakis and L. Pecorelli-Peres, eds.), Electrical and
Computer Engineering Series, pp. 477–483, 2001.
[C23] C. Alippi, S. Ferrari, and V. Piuri, “A methodology for example-based specification
and design,” in Proceedings of IJCNN 2000 (IEEE-INNS-ENNS International Joint
Conference of Neural Networks) (S.-I. Amari, C. L. Giles, M. Gori, and V. Piuri,
eds.), vol. 3, pp. 535–540, July 2000.
[C24] N. A. Borghese and S. Ferrari, “Mesh construction with fast soft vector quantization,” in Proceedings of IJCNN 2000 (IEEE-INNS-ENNS International Joint Conference of Neural Networks) (S.-I. Amari, C. L. Giles, M. Gori, and V. Piuri, eds.),
vol. 5, pp. 473–478, July 2000.
[C25] S. Ferrari, N. A. Borghese, and V. Piuri, “Multi-resolution models for data
processing: an experimental sensitivity analysis,” in Proceedings of IMTC 2000
(17th IEEE Instrumentation and Measurement Technology Conference), vol. 2,
pp. 1056–1060, May 2000.
[C26] N. A. Borghese, S. Ferrari, and V. Piuri, “Local wavelet decomposition and its application to face reconstruction,” in Neural Nets WIRN Vietri-99, Proc. of the 11th Italian Workshop on Neural Nets (M. Marinaro and R. Tagliaferri, eds.), pp. 184–189,
May 1999.
[C27] S. Ferrari and N. A. Borghese, “A portable modular system for automatic acquisition
of 3D objects,” in Proceedings of IMTC’99 (16th IEEE Instrumentation and Measurement Technology Conference) (V. Piuri and M. Savino, eds.), vol. 3, pp. 1823–1827,
May 1999.
[C28] N. A. Borghese and S. Ferrari, “Scanning and reconstruction of human body parts,”
in STAR Proc. of Eurographics 1998, pp. 3.5.1–3.5.2, 1998.
[C29] C. Rigotti, N. A. Borghese, S. Ferrari, G. Baroni, and G. Ferrigno, “Portable and
accurate 3D scanner for breast implants design and reconstructive plastic surgery,” in Proceedings of SPIE’s International Symposium on Medical Imaging 1998,
vol. 3338, pp. 1558–1567, Feb. 1998.
[C30] N. A. Borghese, G. Ferrigno, and S. Ferrari, “Image reconstruction using a hierarchical RBF network architecture,” in Proceedings of WIRN ’97, Italian Workshop
on Neural Nets, pp. 177–182, 1997.
[C31] P. Cerveri, S. Ferrari, and N. A. Borghese, “Calibration of TV cameras through RBF
networks,” in Applications of Soft Computing, Proceedings of SPIE ’97 (B.Bosacchi,
J. Bezdek, and D. Fogel, eds.), vol. 3165, pp. 312–318, 1997.
[C32] M. Fontana, N. A. Borghese, and S. Ferrari, “Image reconstruction using improved
“Neural-Gas”,” in Proceedings of WIRN ’95, Italian Workshop on Neural Nets,
pp. 260–265, 1995.
8
Publications
Other publications
[A1] S. Ferrari and V. Piuri, “Guest editorial special section on VECIMS 2005,” IEEE
Trans. on Instr. and Meas., vol. 57, pp. 1818–1819, Sept. 2008.
[A2] A. E. Saddik, R. Duro, and S. Ferrari, “Guest editorial special section on VECIMS
2006,” IEEE Trans. on Instr. and Meas., vol. 57, pp. 1852–1853, Sept. 2008.
Dissertations
[T1] S. Ferrari, Una Metodologia Gerarchica per Analisi e Sintesi di Immagini
Tridimensionali. PhD thesis, Politecnico di Milano, Jan. 2001.
9