CURRICULUM VITAE DEBORA SLANZI Personal data and contact information Date and place of birth: December 8, 1977, Este (PD) Italy Nationality: Italian Address: Department of Statistics, University Ca Foscari of Venice, San Giobbe, Cannaregio 873, 30121 Venezia, Phone: +39 041 2347441 Fax: +39 041 2347444 Mobile: +39 338 9574508 Email: debora.slanzi@unive.it Web: http://www.dst.unive.it/~debora/ Education Degree and Ph.D. October 1977 October 2002 Degree in Statistics and Economics University of Padova, Thesis: Bayesian Belief Networks: methodologies and techniques for analysing uncertainty (in Italian). January 2003 December 2005 Ph.D. in Statistics University of Padova, Thesis: Bayesian networks: approaches for model selection. Former education 04 17 May 2008 Blueprint for an Artificial Cell Summer school, European Centre for Living Tecnology, Venezia, 31 August 05 September 2007 Evolutionary Computation and Artificial Life SECEVitA 2007 - Summer school, Sampieri (RG), 08 11 November 2004 Graphical Models and Causality Advanced Lectures, Department of Statistics University of Padova, 15 19 June 2004 Statistics and Gene Expression Genomics: Methods and Computation Summer school, Applied Bayesian Statistics 04, Trento, 29 June 04 July 2003 Statistical Inference in Biology and Human Sciences Summer school, University of Asti,
23 28 June 2003 Linear and Non Linear Models and Genetic Algorithms for the Analysis and the Prediction of Time Series Summer school of the Italian Statistical Society, Treviso, Research and Participation to National and International Research Projects Main research interests: Bayesian networks and probabilistic graphical models, statistical model selection, Cluster analysis and multivariate statistical analysis, Design of experiments, Evolutionary computation and optimization, Biostatistics applications. From June 2007 June 2006 May 2007 Research Fellow University Ca Foscari of Venice, Theme of the research: Stochastic models for combinatorial experiments. Research Fellow University Ca Foscari of Venice, Theme of the research: Statistical design and modelling of evolutionary dynamics in biochemical networks. Participation to research projects: DICE Design of Informative Combinatorial Experiments Collaboration to the research project funded by Fondazione Venezia. 2009. Supervisor: Prof. Irene Poli. Evolutionary Computation in Statistics Collaboration to the Italian PRIN 2007 research project, Department of Statistics, University Ca Foscari of Venice, Supervisor: Prof. Irene Poli. PACE Programmable Artificial Cell Evolution Collaboration to the European research project, EU integrated project in FP6-IST-FET, Complex Systems Initiative. 2004-2008. Valutare la valutazione. L impatto della valutazione della didattica nell esperienza universitaria italiana. Uno studio degli indicatori utilizzati Collaboration to the Italian PRIN 2006 research project, Department of Statistics and Economics, University of Pavia, Supervisor: Prof. Stefano Campostrini. Modelli di dipendenza: Bayesian network, learning di struttura, model selection e misure di similarità Statistics, University of Padova, 2005. Tecniche di learning induttivo, valutazione e comparazione di sistemi complessi in un contesto socio-sanitario Statistics, University of Padova, 2004.
Approccio Bayesiano al learning di struttura nel contesto del Bayesian network Statistics, University of Padova, 2003. Visiting positions January February 2005 November December 2005 Aalborg University Visiting Ph.D. Student at the Department of Computer Science. Aalborg University Visiting Ph.D. Student at the Department of Computer Science. Publications G. Minervini, G. Evangelista, L. Villanova, D. Slanzi, D. De Lucrezia, I. Poli, P. L. Luisi, F. Polticelli (2009) Massive non natural proteins structure prediction using grid technologies. BMC Bioinformatics 10(Supp.6): S22. ISSN: 1471-2105. DOI: 10.1186/I471-2105-10-S6-S22. A. Brogini, D. Slanzi (2009) On using Bayesian networks for complexity reduction in decision trees. Statistical Methods and Applications. ISSN: 1613-981X. DOI: 10.1007/S10260-009-0116-1. A. Brogini, D. Slanzi (2009) Several computational studies about variable selections for probabilistic Bayesian classifiers. In C. Lauro, F. Palumbo, M. Greenacre (eds.): Data Analysis and Classification: from Exploration to Confirmation. Series: Studies in Classification, Data Analysis and Knowledge Organization. Springer-Verlag. ISSN: 1431-8814. D. Slanzi, L. Villanova, I. Poli (2009) Gene expression profile patterns in human Cytomegalovirus infections. Working Paper Series n. 1/2009, Venezia, Department of Statistics. A. Brogini, D. Slanzi (2009) Confident Bayesian networks: a non parametric bootstrap approach. In: S. Ingrassia and R. Rocci (eds.) Classification and data analysis 2009. Book of short papers. 437-440. ISBN: 978-88-6129-406-6. I. Poli, D. Slanzi, L. Villanova, D. De Lucrezia, G. Minervini, F. Polticelli (2009) Non natural protein structure identification. In: S. Ingrassia and R. Rocci (eds.) Classification and data analysis 2009. Book of short papers. 597-660. ISBN: 978-88-6129-406-6. D. Slanzi, D. De March, I. Poli (2009) Probabilistic graphical models in high dimensional systems. In S.M. Ermakov, V.B. Melas, A.N. Pepelyshev (eds.): Proceedings of the 6th St. Petersburg Workshop on Simulation. 557-560. St. Petersburg VVM com. Ltd. ISBN: 978-5-9651-0354-6. D. De March, D. Slanzi, I. Poli (2009) Evolutionary Algorithms for Complex Experimental Designs. In S.M. Ermakov, V.B. Melas, A.N. Pepelyshev (eds.): Proceedings of the 6th St. Petersburg Workshop on Simulation. 547-551. St. Petersburg VVM com. Ltd. ISBN: 978-5-9651-0354-6. D. Slanzi, D. De March, I. Poli (2009) Evolutionary Probabilistic Graphical Models in High Dimensional Data Analysis. In F. Mola, C. Conversano, V.E. Vinzi, N. Fisher (eds.): European Regional Meeting of the International Society for Business and Industrial Statistics. Proceedings of the Conference. 124-125. TILAPIA Editore. ISBN: 978-88-89744-13-0.
D. De March, M. Forlin, D. Slanzi, I. Poli (2009) An evolutionary predictive approach to design high dimensional experiments. In R. Serra, I. Poli, M. Villani (eds): Artificial Life and Evolutionary Computation. Proceedings of WIVACE 2008. World Scientific Publishing Company, Singapore. S. Campostrini, L. Bernardi, D. Slanzi (2008) Le determinanti della valutazione della didattica attraverso il parere degli studenti. In Capursi and Ghellini (eds.): Dottor Divago: Discernere valutare e governare la nuova Università. Collana Valutazione - Aiv - Teoria, metodologia e ricerca, Franco Angeli, Milano, 102-122. ISBN: 978 88-464-9634-8. A. Brogini, D. Slanzi (2007) L uso di reti Bayesiane per l analisi di dati statistici multivariati. In A. Grassi (ed.): Demografia e Statistica: un ricordo di Enzo Lombardo tra scienza e cultura. TIPAR Roma Editrice. 57-64. D. Slanzi, I. Poli, D. De March, M. Forlin (2007) Bayesian Networks for Detecting Relevant Variable Interactions for Biochemical Experiments. In: Risk and Prediction, Proceedings of the Intermediate Conference SIS 2007. 661-662. Cleup Editrice, PD. ISBN: 978-88-6129-093-8. D. Slanzi, M. Trevisan, L. Villanova, G. Palù, I. Poli (2007) Bayesian Analysis of Cytomegalovirus Infection from Microarray Data. In: Risk and Prediction, Proceedings of the Intermediate Conference SIS 2007. 535-536. Cleup Editrice, PD. ISBN: 978-88-6129-093-8. M. Forlin, D. De March, D. Slanzi, I. Poli (2007) A Predictive Evolutionary Approach to Design Biochemical Experiments. In: Risk and Prediction, Proceedings of the Intermediate Conference SIS 2007. 659-660. Cleup Editrice, PD. ISBN: 978-88-6129-093-8. D. Slanzi (2007) A Bayesian Network Learning Algorithm for Complex Domains. In P. Mantovan, A. Pastore, S. Tonellato (eds.): Complex Models and Computational Intensive Methods for Estimation and Prediction. Book of Short Papers. 5 th Conference S.Co. 2007. 463-468. Cleup Editrice, PD. ISBN: 978-88-6129-144-0. A. Brogini, D. Slanzi (2007) Several computational studies about variable selection for Bayesian networks. In: Sixth Scientific Meeting of the Classification and Data Analysis Group, CLADAG 2007. Book of Short Papers. 591-594. Macerata, EUM Edizioni. ISBN: 978-88-6056-020-9. M. Bolzan, A. Brogini, D. Slanzi (2005) Apprendimento di Modelli Grafici Esplorativi per la Valutazione in Ambito Socio-Sanitario: il Caso dell Assistenza Informale. Non Profit 1.2005. 207-224. Maggioli Editore. ISSN: 1122-9322. M. Bolzan, A. Brogini, D. Slanzi (2005) I Modelli Grafici Esplorativi per l'analisi del Fabbisogno di Assistenza Ospedaliera Informale. In L. Fabbris (ed.): Efficacia Esterna della Formazione Universitaria: il Progetto OUTCOMES. Atti del Convegno. 375-388. Cleup Editrice, PD. ISBN: 88-7178-692-0. A. Brogini, D. Slanzi (2005) Unsupervised vs Supervised Learning in a Real Complex System. In C. Provasi (ed.): Modelli Complessi e Metodi Computazionali Intensivi per la Stima e la Previsione. S.Co. 2005. Atti del Convegno. 467-472. Cleup Editrice, PD. A. Brogini, M. Bolzan, D. Slanzi (2004). Identifying a Bayesian Network for the problem Hospital and Families. The analysis of patient satisfaction with their stay in hospital. In M. di Bacco, G. D Amore, F. Scalfari (eds.): Applied Bayesian Statistical Studies in Biology and Medicine. Kluwer Academic Publisher, Norwell, MA (USA). Cap.4. ISBN: 978 1-4020-7548-3. Teaching University Ca Foscari of Venice, Italy : Computational Statistics A (Exercise Lessons) Faculty of Economics. 2009.
Statistics I (Exercise Lessons) Faculty of Economics. 2005-2008. Statistics II (Exercise Lessons) Faculty of Economics. 2005-2008. Statistical Models I (Exercise Lessons) Faculty of Economics. 2007. Time Series Analysis I (Exercise Lessons) Faculty of Economics. 2006, 2007. University of Padova, Italy : Statistical Inference I A (Exercise Lessons) Faculty of Statistics. 2004. University of Pavia, Italy : Statistics Faculty of Political Sciences. 2006. Statistics (Exercise Lessons) Faculty of Political Sciences. 2006. Computing abilities Platforms: Programming languages: Statistical Softwares: Text formatting and Office computing: Windows 199x, 2000, XP. Mac Ox. C++. Java. R, Splus. Matlab. Main softwares related to Bayesian networks and graphical models. LaTeX. Office Suite (Word, Excel, PowerPoint, Access).