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People
Stefano Merler
Position
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Senior Researcher |
Current site of work |
Fondazione Bruno Kessler |
Street, number |
via Sommarive 18 |
City |
Povo (Trento) |
Postal code |
38100 |
Country |
Italy |
E-mail |
merler@fbk.eu |
Phone |
+39 0461 314 595 |
Mobile phone |
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Degree, Msc, or PhD; when; where; on what subject; title of the thesis |
Degree; 1994; University of Trento; Mathematics; "A model for the description of a macroparasite infection in a host population with age structure" |
Expertise |
Epidemic models; Biomathematics; Machine Learning |
Professional societies |
GIRPR (Gruppo Italiano Ricercatori in Pattern Recognition) |
Research experience, training, professional stages |
Jul99 – present: Senior Researcher at FBK – MPBA
Jul98 – Jun 99: Researcher at CEA
Jul96 – Jun98: Fellow at CEA
Jan95 – Jun96: Fellow at IRST |
Website |
http://mpba.fbk.eu/merlo |
Current research area |
Mathematical models of the spatio-temporal spread of epidemics |
Publication List (last five years):
S. Merler et al. Coinfection can trigger multiple pandemic waves. Journal of Theoretical Biology, 254(2):499-507, 2008.
M. Ciofi degli Atti et al. Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios. PLoS ONE, 3(3): e1790, 2008.
M. Ajelli and S. Merler. The impact of the unstructured contacts component in influenza pandemic modeling . PLoS ONE, 3(1): e1519, 2008.
A. Barla et al. Machine learning methods for predictive proteomics. Briefings in Bioinformatics, 9:119-128, 2008.
G. Jurman et al. Algebraic stability indicators for ranked lists in molecular profiling. Bioinformatics, 24: 258 - 264, 2008.
S. Paoli et al. Integrating gene expression profiling and clinical data. Int. J of Approximate Reasoning, 47(1):58-69, 2008.
S. Merler et al. Parallelizing AdaBoost by weights dynamics. Computational Statistics and Data Analysis, 51: 2487-2498, 2007.
S. Riccadonna et al. Supervised classification of combined copy number and gene expression data. Journal of Integrative Bioinformatics, 4(3):74, 2007.
M. Cannataro et al. A grid environment for high-throughput proteomics. IEEE Transactions on Nanobioscience, 6(2):117-123, 2007.
S. Merler, G. Jurman, and C. Furlanello. Deriving the kernel from training data. In Multiple Classifier Systems, Lecture Notes in Computer Science, pages 32-41. Springer-Verlag, 2007.
S. Merler, C. Rizzo, M. Ajelli, M. Massari, G. Scalia Tomba, C. Furlanello, and M. L. Ciofi degli Atti. Modelling preventive measures during an influenza pandemic in italy: a real time simulation strategy. In Options for the Control of Influenza VI. Toronto, June 17-23, 2007.
S.Merler, M. Ajelli, G. Jurman, C. Furlanello, C. Rizzo, A. Bella, M. Massari, and M.L. Ciofi degli Atti. Modeling influenza pandemic in italy: an individual based approach. In Proceedings of SIS 2007. Venezia, Italy, June 6-8, 2007.
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.
C. Furlanello et al. Combining feature selection and DTW for time-varying functional genomics. IEEE Transactions on Signal Processing, 54 (6): 2436-2443, 2006.
S. Merler and G. Jurman. Terminated Ramp - Support Vector Machine: a nonparametric data dependent kernel. Neural Network, 19: 1597-1611, 2006.
S. Merler, G. Jurman, C. Furlanello, C. Rizzo, A. Bella, M. Massari, and M.L. Ciofi degli Atti. Strategies for containing an influenza pandemic: the case of italy. In Proceedings of Bionetics, Trento, Italy, December 13-17, 2006, 2006.
A. Barla, B. Irler, S. Merler, G. Jurman, S. Paoli, and C. Furlanello. Proteome profiling without selection bias. In CBMS '06: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems, pages 941-946, Washington, DC, USA, 2006. IEEE Computer Society.
S. Paoli, G. Jurman, D. Albanese, S. Merler, and C. Furlanello. Semisupervised Profiling of Gene Expressions and Clinical Data. In A.G.B. Tettamanzi I. Bloch, A. Petrosino, editor, Fuzzy Logic and Applications: 6th International Workshop, WILF 2005, number 3849 in LNCS, pages 284 - 289. Springer, 2006.
C. Furlanello et al. Semi-supervised learning for molecular profiling. IEEE Transactions on Computational Biology and Bioinformatics, 2(2): 110-118, 2005.
S. Merler, C. Furlanello, and G. Jurman. Machine learning on historic air photographs for mapping risk of unexploded bombs. In F. Roli and S. Vitulano, editors, Lecture Notes in Computer Science, Vol. 3617: 13th International Conference on Image Analysis and Processing (ICIAP2005), pages 735 - 742, 2005.
M. Neteler, D. Grasso, I. Michelazzi, L. Miori, S. Merler, and C. Furlanello. An integrated toolbox for image registration, fusion and classification. International Journal of Geoinformatics. Special Issue on FOSS/GRASS 2004 & GIS-IDEAS 2004, 1(1):51-60, March 2005.
S. Merler et al. Bias-variance control via hard points shaving. International Journal of Pattern Recognition and Artificial Intelligence, 18(5):891-903, 2004.
B. Caprile, S. Merler, C. Furlanello, and G. Jurman. Exact bagging with k-nearest neighbour classifiers. In F. Roli, J. Kittler, and T. Windeatt, editors, Multiple Classifier Systems, Lecture Notes in Computer Science, pages 72-81. Springer, 2004.
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.
M. Neteler, D. Grasso, I. Michelazzi, L. Miori, S. Merler, and C. Furlanello. New image processing tools for GRASS. In Proc. Free/Libre and Open Source Software for Geoinformatics: GIS-GRASS Users Conference 2004, Sept. 12-14, Bangkok, Thailand, 2004.
C. Furlanello et al. An accelerated procedure for recursive feature ranking on microarray data. Neural Networks, 16(5-6): 641-648, 2003.
C. Furlanello et al. Entropy-Based Gene ranking without selection bias for the predictive classification of microarray data. BMC Bioinformatics, (4):54, 2003.
S. Merler et al. Automatic model selection in cost-sensitive boosting. Information Fusion, 4(1):3-10, 2003.
C. Furlanello, M. Serafini, S. Merler, and G. Jurman. Advances in Neural Network Research: IJCNN 2003, chapter An accelerated procedure for recursive feature ranking on microarray data. Elsevier, 2003.
C. Furlanello, M. Serafini, S. Merler, and G. Jurman. Control of selection bias in microarray data analysis. Minerva Biotecnologica, 15(4):217-222, 2003.
C. Furlanello, M. Neteler, S. Merler, S. Menegon, S. Fontanari, A. Donini, A. Rizzoli, and C. Chemini. GIS and the Random Forest Predictor: Integration in R for Tick-borne Disease Risk Assessment. In K. Hornik and F. Leisch, editors, Proceedings of the 3rd International Workshop on Distributed Statistical Computing, Vienna, Austria, March 20-22, 2003.
C. Furlanello, M. Serafini, S. Merler, and G. Jurman. Gene selection and classification by Entropy-based Recursive Feature Elimination. In International Joint Conference on Neural Networks, pages 3077-3082, Portland, Oregon, July 20-24, 2003.
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