Salvatore Ingrassia


Professor of Statistics
Department of Economics and Business
University of Catania

Corso Italia, 55, 95128, Catania, Italy. 
Tel: +(39) 0957537732
Email: s.ingrassia@unict.it
Web: http://www.dei.unict.it/salvatore.ingrassia
ORCID: orcid.org/0000-0003-2052-4226


Curriculum Vitae: Download CV


Education
Research Fellow, Département d’Intelligence Artificielle et Mathématiques (DIAM), Ecole Normale Supérieure de Cachan (France), 1993-1994.
Ph.D. in Applied Mathematics and Computer Science, University of Naples (Italy), 1991; Ph.D. Thesis: Spectra of Markov chains and optimization algorithms (Spettri di catene di Markov e algoritmi di ottimizzazione).
Degree in Electrical Engineering, University of Catania (Italy), 1986.
 


Research Interests
Model-based clustering, mixture models, computational statistics, neural networks, stochastic algorithms
 


Editorial Board Memberships
  • Statistical Methods and Applications: Associate Editor, 2013 to present.
  • Advances in Data Analysis and Classification: Associate Editor, 2014 to present.
  • Computational Statistics and Data Analysis: Associate Editor, 2015 to present.
  • Silesian Statistical Review: member of the Editorial Board, 2016 to present.
     
  Guest Editorships
  • Advances in Data Analysis and Classification, special issue on "Advances on Model-Based Clustering and Classification", Guest Editors: Sylvia Frühwirth-Schnatter, Salvatore Ingrassia, Agustín Mayo-Iscar, 12(1), 2019.
  • Econometrics and Statistics, "Third Special Issue on Mixture Models", Guest Editors: John Hinde, Salvatore Ingrassia, Tsung-I Lin and Paul McNicholas, 2017.
  • Advances in Data Analysis and Classification, special issue on "New Trends on Model-Based Clustering and Classification", Guest Editors: Gérard Govaert, Salvatore Ingrassia, Geoff McLachlan, 9(4), 2016.
  • Computational Statistics and Data Analysis, 3rd special issue on "Advances in Mixture Models", Guest Editors: John Hinde, Salvatore Ingrassia, Tsung-I Lin and Paul McNicholas, 93, 2016.
  • Advances in Data Analysis and Classification, special issue on "Model Based Clustering and Classification", Guest Editors: Hans-Hermann Bock, Salvatore Ingrassia and Jeroen Vermunt, 7(3), 2013 and 8(1), 2014.

Institutional Responsibilities
  • Quality Assurance Chief Officer at University of Catania (from 2017)
  • Member of the Board of Directors of the "International Association for Statistical Computing" of the International Statistical Institute (2016-2020).
  • President of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (2015-2017).
  • Vice-President of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (2013-2015).
  • Deputy-Head of Department of Economics and Business, University of Calabria (2012-2015).
  • Head of the Department of Business and Management, University of Catania (2010-2012).
  • President of the Scientific Advisory Board of “Economics and Statistics”, University of Catania (2009-2011).
  • Deputy-Head of Department of Economics and Statistics, University of Calabria (2003-2005).
  • Teaching Director, Master in Statistics, University of Calabria (2003-2005).
  • Teaching Director, B.A. in Statistics, University of Calabria (2001-2005).

 


Main Publications

  2015-2019

 
2010-2014

 
2004-2009

 
2000-2004

  • Ingrassia S. (2004). A Likelihood-Based Constrained Algorithm for Multivariate Normal Mixture ModelsStatistical Methods and Applications13 (2), 151-166.
  • Costanzo G.D., Ingrassia S. (2004). Analysis of the MIB30 basket in the period 2000-2002 by functional PC's, in “J. Antoch (Ed.), Proceedings of COMPSTAT 2004 Symposium”, Physica-Verlag, 807-814.
  • Ingrassia S., Morlini I. (2004). On the degrees of freedom in richly parameterised models, in “J. Antoch (Ed.), Proceedings of COMPSTAT 2004 Symposium”, Physica-Verlag, 1237-1244.
  • Cerioli A., Ingrassia S., Corbellini A. (2004). Classificazione simbolica di dati funzionali: un'applicazione al monitoraggio ambientale, in “C. Lauro & C. Davino (a cura di), Data Mining e Analisi Simbolica”, Franco Angeli Editore, Milano, 2004, 31-64.
  • Ingrassia S., Cerioli A.,  Corbellini (2003) A. Some Issues on clustering of functional data, in “M. Schader, W. Gaul, and M.Vichi (Eds.), Between Data Science and Applied Data Analysis”,Springer-Verlag, 49-56.
  • Ingrassia S., Davino C. (a cura di) (2002). Reti Neuronali e Metodi Statistici, Franco Angeli Editore, Milano.
  • Ingrassia S., Morlini I. (2002). Modelli neuronali per piccoli insiemi di dati, in “N.C. Lauro & G. Scepi (a cura di), Analisi Multivariata per la Qualità Totale. Metodologia,
    aspetti computazionali ed applicazioni
    ”,Franco Angeli Editore, 29-40.
  • Cavarra S., Crupi V., Guglielmino E., Ingrassia S. (2001). Reti Neurali per la rilevazione di anomalie da dati vibrometrici: un caso studio, Statistica Applicata13(1), 5-16.
  • Domma F., Ingrassia S. (2001). Mixture models for maximum likelihood estimation from incomplete values, in “S. Borra, R. Rocci, M.Vichi and M. Schader (Eds.), Studies in Classification, Data Analysis and Knowkedge Organization”, Springer-Verlag, 201-208.
  • Gilio A., Ingrassia S. (2000). Extension of totally coherent interval-valued probability assessment, in “B. Bouchon-Meunier, R.R. Yager and L.A. Zadeh (Eds.), Uncertainty in Intelligent and Information Systems”, World Scientific, 80-91.

 
1991-1999

  • Ingrassia S. (1999). Geometrical aspects of discrimination by multilayer perceptronsJournal of Multivariate Analysis68, 226-234.
  • Ingrassia S. (1999). Logistic discrimination by Kullback-Leibler type distance measures, in “M.Vichi and O.Opitz (Eds.), Classification and Data Analysis”, Springer-Verlag, (1999), 89-96.
  • Gilio A., Ingrassia S. (1998). Totally coherent set-valued probability assessmentsKybernetika34(1), 3-15.
  • Ingrassia S. (1998). A note on the approximation by superposition of sigmoidal functions, in “A. Bellacicco e A. Laforgia (a cura di), Funzioni Speciali e Applicazioni”, Franco Angeli Editore, 57-67.
  • Ingrassia S. (1997). On the realization of discriminant functions by means of multilayer perceptrons, MetronLV (3-4), 185-200.
  • Ingrassia S. (1997). Sulle proprietà discriminanti delle trasformazioni sigmoidali, in in “A. Bellacicco e N.C. Lauro (a cura di), Reti Neurali e Statistica”, Franco Angeli Editore, 99-108.
  • Ingrassia S., Mammana M.L., Commis E. (1997). Internet in Italia: un’indagine statistica, Annali della Facoltà di Economia dell’Università di CataniaXLI, 175-199.
  • Torrisi A., Ingrassia S., et al. (1996). A study of greek pottery and clay statuettes from the votive deposit in the sanctuary of Demetra in Catania, Annali di Chimica86, 329-341.
  • Ingrassia S., Commis E. (1994). A neural network approach to defect detection in oranges, Le Matematiche48(2), 273-286.
  • Ingrassia S., Anile A.M., Commis E. (1994). Defect discrimination in citrus via neural network, in “A. Fasano e M. Primicerio (Eds.), Proceedings of the Seventh European Conference on Mathematics in Industry”,
    B.G. Teubner, Stuttgart, 239-246.
  • Ingrassia S. (1994). On the rate of convergence of the Metropolis algorithm and the Gibbs sampler by geometric boundsThe Annals of Applied Probability, 4(2), 347-389.
  • Ingrassia S. (1993). Geometric approaches to the estimation of the spectral gap of reversible Markov chainsCombinatorics, Probability & Computing2(3), 301-323.
  • Ingrassia S. (1992). A comparison between the simulated annealing and the EM algorithms in normal mixture decompositionsStatistics and Computing2(4), 203-211.
  • Ingrassia S. (1991). Mixture decomposition via the simulated annealing algorithmApplied Stochastic Models and Data Analysis7 (4), 317-325.