August 22, 2005 Cesare Furlanello

Cesare Furlanello received his degree in Mathematics at the University of Padua, Italy, in 1986. He is at Fondazione Bruno Kessler (FBK) since 1987, now a Senior Researcher. He is currently head of the MPBA Research Unit, and previously of the ITC-irst Neural Network for Complex Data Analysis Project, since 1995.

His main research interests are in the application of machine learning methods to medical and environmental data.

Peer reviewed papers: total 82; intnl journals: 39 Book Chapters: 5; natl journals: 8; Int. congresses with review: 30. Invited lectures (Intl): 14. For CV and other information please browse at the following links, or below in this page:

A recent ShortBio in FBK Format (Mar 2009)

Complete Bio (Mar 2009)

A MITRIS PROJECT TechRep (New PPT for UNPSA 2008 - Feb 2008)

MPBA papers

He has designed and managed many studies and projects involving interdisciplinary collaboration with life science researchers. He was Project manager at ITC/IRST for the National Bioelectronics Project (1991-94). He is currently project manager of several national or regional research projects in the field of Predictive Models applied to Environmental and Medical data Analysis. These studies combine existing and new methods from statistical machine learning methods with new sw infrastructures for data collection, management and distribution of the resulting models. The most recent research is directed to applications in functional genomics.

Basic and applied studies have been developed at the MPBA group with colleagues in other institutions on vector-borne disease mapping, wildlife epidemiology, traffic safety, landscape risk analysis. In order to support these studies, CF has actively contributed to the development of computational methods, supporting the development of open source geoinformatics (GIS GRASS, WebGIS) and recently grid sw (BioDCV). Since 2002, he has contributed to the development of predictive classification models and gene selection procedures for molecular diagnostics, in collaboration with national and international centres of excellence in molecular oncology. He is an investigator in one project of AIRC for the development of the Italian integrated platform for bioinformatics, with the IFOM-FIRC institute.

Several of the systems realized in experimental studies are now data management infrastructures for public agencies: MITRIS (Trentino and Friuli-VG), UXB-TN (Trentino), FaunaTN and FaunaBL (Trentino and Belluno) are the largest. The spinoff company MPA Solutions is mantaining these systems and developing WebGIS technologies with predictive modeling functions.

CF was Scientific secretary of the GNCB-CNR school on Neural Networks for Signal Processing (Trento 1989) and of several other workshops on Applications of Machine Learning and Neural Networks. In September 2008, he was Local Conference Chair of the MGED11 International Workshop of the MGED Society (in its Advisory Board since 2007). Lecturer on Neural Network and Statistics at Master School of Advanced Information Science of Salerno University. Chairman of Session Theory 1 at IEEE NNSP-95 Cambridge MA, 1995. Member of the Scientific Board of the Multiple Classifier Systems series of conferences. Invited participant in the Machine Learning and Neural Networks Program of the Newton Institute of Mathematical Science, Cambridge UK, 1998. Member of the Italian Neural Network Society (serving in its Scientific Board 1991-2005), of the International Association for Pattern Recognition.

Invited lectures (a selection): NATO-ASI school Learning with Ensemble models (Vietri 2002), the ECEM/EAML Conference (Bled 2004), at the Int. BCB-Workshop on Machine Learning in Bioinformatics (Oct. 2005, Berlin), Int. School "The analysis of patterns" (Nov. 2005, Erice), "Predictive modeling on spatio-temporal patterns" (April 2007, Univ. Bristol), and "Signature Stability Analysis" (Nov 2007, Silver Springs, FDA).

He has been supervisor of 30 graduate or postgraduate theses for the universities of Trento (Mathematics and Engineering), Milano, Bologna, and Torino, supervisor of 3 Leonardo graduate placements in 2002, tutor of 3 ASI-CONAE fellows in 2003-2005. Currently a supervisor of internships for Master thesis in Mathematics, Information and Telecommunication Engineering for the University of Trento. In 2003-2005, a tutor for a post-doc fellowship in Bioinformatics sponsored by PAT. A collection of teaching material and a list of recently supervised theses are available at the TEACHING group page. For a synopsis here: 1998-2003: Lecturer on "COMPUTATIONAL STATISTICS AND PREDICTIVE MODELS", a course of the Math Department of Trento University, and 2004-06: Lecturer on "Statistical Machine Learning", a course for the International Graduate School in Information and Communication Technologies, Trento University.

He is a founder of the WEBVALLEY project, the FBK summer course for dissemination of interdisciplinary scientific research. Since 2001, CF is responsible for the WebValley Scientific program, and a resident tutor for all the 7 editions of this event (history). Developing the culture of data with open source platforms (web scripting, geodatabases, webGIS, tools for data visualization, statistical analysis decision making) based on a challenging project is the theme of 3 fast-paced weeks, in which about 20 high schools students team up with senior and junior researchers. The goal of WebValley 2004 was the development of an integrated web platform for GIS-genetics research. The WEBVALLEY 2005 Camp , dealt with "High performance computing for the scientific visualization of geolocated biological-environmental data (Pieve di Bono, Trentino, June 27 - July 16, 2005). In 2006, an environmental informatics application was developed for solar energy map modeling, while the 2007 project drafted a prototype WebGIS system for mapping refugees and returnees in West Darfur for UN-HCR (with the humanitarian ngo INTERSOS and MPBA's spinoff MPA Solutions). Read more about WebValley .

SELECTED PUBLICATIONS

1. MACHINE LEARNING FOR FUNCTIONAL GENOMICS & BIOINFORMATICS

  • J.P.A. Ioannidis, D.B. Allison, C.A. Ball, I. Coulibaly, X. Cui, A.C. Culhane, M. Falchi, C. Furlanello, L. Game, G. Jurman, T. Mehta, J. Mangion, M. Nitzberg, G.P. Page, E. Petretto, V. van Noort. Replication of published microarray gene expression analyses. Nature Genetics, Feb:41(2):135, 2009

  • A. Barla, G. Jurman, S. Riccadonna, M. Chierici, S. Merler, and C. Furlanello. Machine learning methods for predictive proteomics. Briefings in Bioinformatics, 9(2), 119-128, 2008.

  • G. Jurman, S. Merler, A. Barla, A. Galea, C. Furlanello. Algebraic stability indicators for ranked lists in molecular profiling. Bioinformatics, 24(2):258-264, 2008.

  • S. Riccadonna, G. Jurman, S. Merler, S. Paoli, A. Quattrone, and C. Furlanello. Supervised classification of combined copy number and gene expression data. Journal of Integrative Bioinformatics, 4(3):74:177-188, 2007.

  • M. Cannataro, A. Barla, R. Flor, A. Gallo, G. Jurman, S. Merler, S. Paoli, G. Tradigo, P. Veltri, and C. Furlanello A grid environment for high-throughput proteomics, IEEE Trans. on Nanobiosciences, 6(2):117-123, 2007.

  • C. Furlanello, S. Merler, and G. Jurman. Combining feature selection and DTW for time-varying functional genomics. IEEE Transactions on Signal Processing, 54(6):2436-2443, 2006.

  • C. De Pitta, L. Tombolan, G. Albiero, F. Sartori, C. Romualdi, G. Jurman, M. Carli, C. Furlanello, G. Lanfranchi, and A. Rosolen. Gene expression profiling identifies potential relevant genes in alveolar rhabdomyosarcoma pathogenesis and discriminates PAX3-FKHR positive and negative tumors. Int J Cancer. 2005 Dec 27; [Epub ahead of print] PMID: 16381018

  • C. Furlanello, M. Serafini, S. Merler, and G. Jurman. Semi-supervised learning for molecular profiling. IEEE Transactions on Computational Biology and Bioinformatics, 2(2):110-118, 2005. 2005.

  • C. Furlanello, M. Serafini, S. Merler, and G. Jurman. Methods for predictive classification and molecular profiling from DNA microarray data. Ital. Heart J., 5(1):199-202, 2004.

  • C. Furlanello, M. Serafini, S. Merler, and G. Jurman. Entropy-Based Gene Ranking without Selection Bias for the Predictive Classification of Microarray Data. BMC Bioinformatics, (4):54, 2003.

  • C. Furlanello, M. Serafini, S. Merler, and G. Jurman. An accelerated procedure for recursive feature ranking on microarray data. Neural Networks, volume 16(5-6) pp. 641-648, 2003.

  • A. Barla, B. Irler, S. Merler, G. Jurman, S. Paoli, and C. Furlanello. Proteome profiling without selection bias. In Proc. of IEEE-CMBS 2006 , 2006.

  • S.Paoli, G. Jurman, D. Albanese, S. Merler and C. Furlanello Integrating gene expression profiling and clinical data Int. J. of Approx. Reasoning, in press 2007

    • 2. MACHINE LEARNING FOR ECOLOGY AND LANDSCAPE EPIDEMIOLOGY

  • M. Ciofi degli Atti, S. Merler, C. Rizzo, M. Ajelli, M. Massari, P. Manfredi, C. Furlanello, G. Scalia Tomba, and M. Iannelli. Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PLoS ONE, In press, 2008

  • M. L. Ciofi degli Atti, C. Rizzo, A. Bella, M. Massari, M. Iannelli, A. Lunelli, A. Pugliese, J. Ripoll, P. Manfredi, G. Scalia Tomba, S. Merler, G. Jurman, and C. Furlanello. Modelling scenarios of diffusion and control of pandemic influenza, Italy. Euro Surveill., 12(1):E070104.2, 2007

  • Marta Benito Garzon, Radim Blazek, Markus Neteler, Rut Snchez de Dios, Helios Sainz Ollero, and Cesare Furlanello. Predicting habitat suitability with Machine Learning models: the potential area of Pinus sylvestris L. in the Iberian Peninsula. Ecological Modelling , 197(3-4):383-393, August 2006

  • C. Furlanello, M. Neteler, S. Merler, S. Menegon, S. Fontanari, A. Donini, A. Rizzoli, and C. Chemini. GIS and the randomForest Predictor: integration in R for tick-borne disease risk assessment. Distributed Statistical Processing 2003, Wien, 21 March, 2003.

  • A. Rizzoli, S. Merler, C. Furlanello, and C. Genchi. Geographical information system and bootstrap aggregation (bagging) of tree-based classifiers for lyme disease risk assessment in Trentino, Italian Alps. Journal of Medical Entomology, 39(3):485-492, 2002.

  • G.R. Hess, S.E. Randolph, P. Arneberg, C. Chemini, C. Furlanello, J. Harwood, M. Roberts, and J. Swinton. Spatial aspects of disease dynamics. In J. Hudson, A. Rizzoli, B.T. Grenfell, H. Heesterbeek, and A. P. Dobson, editors, The Ecology of Wildlife Diseases, pages 102-118. Oxford University Press, 2002.

  • C. Furlanello, S. Merler, S. Menegon, S. Mancuso, and G. Bertiato. New WEBGIS technologies for geolocation of epidemiological data: an application for the surveillance of the risk of Lyme borrelliosis disease. G. It. Aritm. e Cardiost., 5(1):241-245, 2002.

  • Furlanello C., Merler S. 2000 "Boosting of Tree-based Classifiers for Predictive Risk Modeling in GIS" In Roli F. (ed), First International Workshop on Multiple Classifier Systems, Lecture Notes in Computer Sciences, Springer Verlag.

  • Furlanello C., Merler S., Rizzoli A., Chemini C., Genchi C. "Bagging as a predictive method for landscape epidemiology of Lyme disease". G. Ital. Cardiol. Suppl 5. 1999

  • Furlanello C., Merler S., and Chemini C., 'A new bootstrap mehod for risk assessment of exposure to Lyme disease'. G. Ital. Cardiol, Vol 28, Suppl. 1, 1998, 167-171.

  • Furlanello C., Merler S., and Chemini C., 'Tree-based Classifiers and GIS for Biological Risk Forecasting'. In Morabito F.C. (ed), Advances in Intelligent Systems, 1997, IOS Press Amsterdam, 316-323.

  • Bonavita P., Chemini C., Ambrosi P., Minerbi F., Salvadori C., Furlanello C. 'Biodiversity and Stress Level in Four Forests of the Italian Alps'. Chemosphere , 1997.

  • Merler S., Furlanello C., Chemini C., Nicolini G., 'Classification Tree Methods for Analysis of Mesoscale Distribution of Ixodes ricinus (Acari: Ixodidae) in Trentino, Italian Alps', Journal of Medical Entomology, 33(6) 1996, 888-893.

  • Chemini C., Rizzoli A., Merler S., Furlanello C., Genchi C. 'Ixodes Ricinus Acari: Ixodidae) Infestation on Roe Deer (Capreolus Capreolus) in Trentino, Italian Alps'. Parassitologia, 39 (1), 1997.

  • Furlanello C., Merler S., Chemini C. and Rizzoli A., 'An Application of the Bootstrap 632+ Rule to Ecological Data', in Marinaro M. and Tagliaferri R. (eds) Neural Nets WIRN-97, MIT Press, 1998.

    • 3. MACHINE LEARNING AND SENSORY ANALYSIS

  • P. M. Granitto, F. Gasperi, F. Biasioli, E. Trainotti & C. Furlanello, "Modern data mining tools in descriptive sensory analysis: a case study with a Random Forest approach", Food Quality and Preferences , 18(4):681-689, 2007.

  • P. Granitto, C. Furlanello, F. Biasioli, and F. Gasperi. Recursive Feature Elimination with Random Forest for PTR-MS analysis of agroindustrial products. Chemometrics and Intelligent Laboratory Systems , 83(2):83-90, 2006.

  • Pablo M. Granitto, Franco Biasioli, Eugenio Aprea, Daniela Mott, Cesare Furlanello, Tilmann D. Mrk, and Flavia Gasperi. Rapid and non-destructive identification of strawberry cultivars by direct ptr-ms headspace analysis and data mining techniques. Sensors & Actuators: B. Chemical, 121(2):379-385, 2007. [ bib ]

    • 4. STATISTICAL MACHINE LEARNING

  • S. Merler, B. Caprile, and C. Furlanello. Parallelizing AdaBoost by weights dynamics. Computational Statistics and Data Analysis , 51(5):2487-2498, 2007.
  • S. Merler, C. Furlanello, B. Larcher, and A. Sboner. Automatic model selection in cost-sensitive boosting. Information Fusion, 4(1):3-10, 2003.

  • S. Merler, B. Caprile, and C. Furlanello. Bias-variance control via hard points shaving. International Journal of Pattern Recognition and Artificial Intelligence, 2004. 18(5):1-13

  • B. Caprile, C. Furlanello, and S. Merler. Highlighting hard patterns via Adaboost weights evolution. In J. Kittler and F. Roli, editors, Multiple Classifier Systems, Lecture Notes in Computer Science 2364, pages 72-80. Springer, 2002.

  • Merler S., Furlanello C., 'Selection of Tree-based Classifiers with the Bootstrap 632+ Rule'. Biometrical Journal, 39(2), 1997, 1-14.

    • 5. STATISTICAL MACHINE LEARNING: OTHER APPLICATIONS

  • P. Fateh-Moghadam, G. Dallago, S. Piffer, G. Zanon, S. Menegon, S. Fontanari, and C. Furlanello. Epidemiology of Road Traffic Accidents in the province of Trento: first results of an integrated surveillance system (MITRIS). Epidemiol Prev. , 29(3-4):172-179, 2005.

  • Furlanello F., Bertoldi A., Dallago M., Furlanello C., Fernando F., Inama G., Pappone C., Chierchia A., 'Cardiac Arrest and Sudden Death in Competitive Athletes with Arrhythmogenic Right Ventricular Dysplasia'. PACE , Vol. 21, No. 1, Part II, 331--335, 1998.

  • M. Neteler, D. Grasso, I. Michelazzi, L. Miori, S. Merler, and C. Furlanello. An integrated toolbox for image registration, fusion and classification. Int. J. of Geoinformatics, 1(1):51-60, March 2005

  • M. Visentin and C. Furlanello. Time series boosting for the automatic selection of panels in marketing studies. In M. Corazza, editor, Rendiconti per gli studi economici Quantitativi, 2001.

  • Furlanello C., Giuliani D., Trentin E., Merler S., 'Speaker Normalization and Model Selection of Combined Neural Nets', Connection Science , 9(1), 1997, 31-50.

    • DIVULGATIVE

  • Furlanello C., Visentin S. 2000 "Algoritmi boosting e applicazioni alla selezione automatica di panel", Scienza e Business, n 1-2 (2), April.



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