Membro del CMCS

Università: Università degli Studi di Ferrara

Carica: professore

E-mail: yannick.tazzari@unife.it

Pagina web

Tematiche di ricerca: Legge di Benford - Manipolazione dati - First-digit - Invarianza di scala

Alcune pubblicazioni:

• Y. Tazzari, S. Bonnini, G. Marzo. Benford’s Law: genesi, letteratura e applicazioni empiriche. Quaderni del Dipartimento DEM, vol.9, n.1, Università degli Studi di Ferrara, Ferrara, 2020.

Membro del CMCS

Università: Università degli Studi di Ferrara

Carica: professore

E-mail: walter.boscheri@unife.it

Pagina web

Tematiche di ricerca: Meccanica computazionale dei fluidi e dei solidi - Metodi numerici ad alto ordine: Volumi finiti e DG - Griglie non strutturate - Schemi Lagrangiani - Asymptotic and structure preserving methods.

Alcune pubblicazioni:

Membro del consiglio direttivo

Università: Università degli Studi di Ferrara

Carica: professore associato

E-mail: valerio.caleffi@unife.it

Pagina web

Tematiche di ricerca: Meccanica dei fluidi - Fluidodinamica computazionale - Emodinamica computazionale - Metodi numerici.

Alcune pubblicazioni:

• G. Bertaglia, V. Caleffi, L. Pareschi, A. Valiani. Uncertainty quantification of viscoelastic parameters in arterial hemodynamics with the a-FSI blood flow model. Journal of Computational Physics, vol. 430, art. 110102, 2021;

• G. Bertaglia, M. Ioriatti, A. Valiani, M. Dumbser, V. Caleffi. Numerical methods for hydraulic transients in visco-elastic pipes. Journal of Fluids and Structures, vol. 81, pp. 230- 254, 2018;

• F. Carraro, D. Vanzo, V. Caleffi, A. Valiani, A. Siviglia. Mathematical study of linear morphodynamic acceleration and derivation of the MASSPEED approach. Advances in Water Resources, vol. 117, pp. 40-52, 2018.

• V. Caleffi, A. Valiani, A. Bernini. Fourth-order balanced source term treatment in central WENO schemes for shallow water equations. Journal of Computational Physics, vol. 218, pp. 228–245, 2006;
• A. Valiani, V. Caleffi, A. Zanni. Case Study: Malpasset Dam-Break Simulation using a Two-Dimensional Finite Volume Method. Journal of Hydraulic Engineering, vol. 128, pp. 460–472, 2002.

Docente: Walter Boscheri

Membro del consiglio direttivo

Università: Università degli Studi di Ferrara

Carica: professore associato

E-mail: stefano.bonnini@unife.it

Pagina web

Tematiche di ricerca: Statistica multivariata - Test di permutazione - Indicatori compositi - Test di permutazione combinati - Test multipli.

Alcune pubblicazioni:

• R. Alfieri, S. Bonnini, C. Brombin, C. Castoro, L. Salmaso. Iterated combination-based paired permutation tests to determine shape effects of chemotherapy in patients with esophageal cancer. Statistical Methods in Medical research, vol. 25, pp. 598-614, 2016;
• S. Bonnini. Multivariate approach for comparative evaluations of customer satisfaction with application to transport services. Communication in Statistics: Simulation and Computation, vol. 45, pp. 1554-1568, 2016;
• G.R. Arboretti, S. Bonnini, L. Corain, D. Vidotto. Environmental Odor Perception: testing regional differences on heterogeneity with application to odor perceptions in the area of Este (Italy). Environmetrics, vol. 26, pp. 418-430, 2015;
• G.R. Arboretti, S. Bonnini, L. Corain, L. Salmaso. A Permutation Approach for Ranking of Multivariate Populations. Journal of Multivariate Analysis, vol. 132, pp. 39-57, 2014;
• S. Bonnini. Testing for heterogeneity with categorical data: permutation solution vs. bootstrap method. Communication in Statistics: Theory and Methods, vol. 43, pp. 906-917, 2014;
• G.R. Arboretti, S. Bonnini, F. Pesarin. A permutation approach for testing heterogeneity in two-sample problems. Statistics and Computing, vol. 19, pp. 209-216, 2009.

Membro del CMCS

Università: Università degli Studi di Ferrara

Carica: dottoranda

E-mail: sara.grassi@unife.it

Tematiche di ricerca: Analisi Numerica - Swarm-based and Consensus-based methods for Global Optimization - Apprendimento Automatico.

Alcune pubblicazioni:

• S. Grassi, L. Pareschi. From particle swarm optimization to consensus based optimization: stochastic modeling and mean-field limit. arXiv preprint arXiv:2012.05613, 2020.

Area 1

• G. Bertaglia, L. Pareschi. Hyperbolic models for the spread of epidemics on networks: kinetic description and numerical methods. ESAIM: Mathematical Modelling and Numerical Analysis, vol. 55, pp. 381-407, 2021;

• G. Dimarco, L. Pareschi, G. Toscani, M. Zanella. Wealth distribution under the spread of infectious diseases. Physical Review, vol. 102, 2020;

• G. Dimarco, A. Tosin. The Aw-Rascle traffic model: kinetic derivation and generalisations. Journal of Statistical Physics, Num. 178, vol. 1, pp. 178-210, 2020;

• M. Herty, L. Pareschi, G. Visconti. Mean field models for large data-clustering problems. Networks and Heterogeneous Media, vol. 15, pp. 463–487, 2020;

• B. Piccoli, A. Tosin, M. Zanella. Model-based assessment of the impact of driver-assist vehicles using kinetic theory. Zeitschrift für Angewandte Mathematik und Physik, vol. 71, Art. 152, 2020;

• G. Albi, N. Bellomo, L. Fermo, S.Y. Ha, J. Kim, L. Pareschi, D. Poyato, J. Soler. Vehicular traffic, crowds, and swarms: from kinetic theory and multiscale methods to applications and research perspectives. Mathematical Model and Methods in Applied Sciences, vol. 29, pp. 1901–2005, 2019;

• T. Trimborn, L. Pareschi, M. Frank. Portfolio optimization and model predictive control: a kinetic approach. Discrete and Continuous Dynamical Systems, Ser. B, vol. 24, pp. 6209–6238, 2019;

• G.M. Assegie. Modeling Volatility Spillovers from Developed Stock Markets to Selected African Stock Markets. ኢ ስ ታ ማመ: 1.

Area 2

• D. Azzolini, F. Riguzzi, E. Lamma. A semantics for hybrid probabilistic logic programs with function symbols. Artificial Intelligence, vol. 294, art. 103452, 2021;

• S. Bonnini, G. Mazzoni, M. Borghesi, G. Chiaranda, J. Myers, S. Mandini, A. Raisi, S. Masotti, S. Grazzi. Improving walking speed reduces hospitalization costs in outpatients with cardiovascular disease. An analysis based on a multistrata non-parametric test. BMC Health Services Research, vol. 20, Art. 1048, 2020;

• F. Riguzzi, E. Bellodi, R. Zese, M. Alberti, E. Lamma. Probabilistic inductive constraint logic. Machine Learning, 2020;

• M. Borghesi. Metodi statistici per il confronto di serie storiche con applicazioni finanziarie. Quaderni del Dipartimento DEM, vol.9, n.4, Università degli Studi di Ferrara, Ferrara, 2020;

• M. Borghesi, M. Brunori. Specializzazione economica: concetto e misure. Quaderni del Dipartimento DEM, vol.9, n.5, Università degli Studi di Ferrara, Ferrara, 2020;

• Y. Tazzari, S. Bonnini, G. Marzo. Benford’s Law: genesi, letteratura e applicazioni empiriche. Quaderni del Dipartimento DEM, vol.9, n.1, Università degli Studi di Ferrara, Ferrara, 2020;

• M. Pelegrín, E. Muñoz-Velasco, P. Sala, G. Sciavicco, I.E. Stan. On Coarser Interval Temporal Logics. Artificial Intelligence, vol. 266, pp. 1- 26, 2019;

• S. Bonnini, M.G. Assegie. Permutation multivariate tests for treatment effect: theory and recent developments. SUSAN SSACAB 2019. The Biostatistics Research Unit of the South African Medical Research Council, 2019;

• F. Jiménez, A. Paoletti, G. Sánchez, G. Sciavicco. Predicting the Risk of Academic Dropout with Temporal Multi-Objective Optimization. IEEE Transactions on Learning Technologies, vol. 12, pp. 225- 236, 2019;

• F. Riguzzi. Foundations of Probabilistic Logic Programming. River Publishers, Gistrup, Denmark, 2018;

• F. Jiménez, C. Martínez, L. Miralles, G. Sánchez, G. Sciavicco. Multi-Objective Evolutionary Rule-Based Classification with Categorical Data. Entropy, vol. 20, art. 684, 2018.

Area 3

• L. Preziosi, G. Toscani, M. Zanella. Control of tumor growth distributions through kinetic methods. Journal of Theoretical Biology, vol. 514, art. 110579, 2021;

• G. Bertaglia, V. Caleffi, L. Pareschi, A. Valiani. Uncertainty quantification of viscoelastic parameters in arterial hemodynamics with the a-FSI blood flow model. Journal of Computational Physics, vol. 430, art. 110102, 2021;
• G. Bertaglia, V. Caleffi, A. Valiani. Modeling blood flow in viscoelastic vessels: the 1D augmented fluid-structure interaction system. Computer Methods in Applied Mechanics and Engineering, vol. 360, art. 112772, 2020;

• G. Bertaglia, A. Navas-Montilla, A. Valiani, M.I. Monge Garcia, J. Murillo, V. Caleffi. Computational hemodynamics in arteries with the one-dimensional augmented fluid-structure interaction system: viscoelastic parameters estimation and comparison with in-vivo data. Journal of Biomechanics, vol. 100, art. 109595, 2020;

• J. Kamínska, E. Lucena-Sánchez, G. Sciavicco. Temporal Aspects in Air Quality Modelling - A Case Study in Wroclaw. Air, Soil, and Water Research, vol. 13, 2020;

• G. Bertaglia, M. Ioriatti, A. Valiani, M. Dumbser, V. Caleffi. Numerical methods for hydraulic transients in visco-elastic pipes. Journal of Fluids and Structures, vol. 81, pp. 230- 254, 2018;

• F. Carraro, D. Vanzo, V. Caleffi, A. Valiani, A. Siviglia. Mathematical study of linear morphodynamic acceleration and derivation of the MASSPEED approach. Advances in Water Resources, vol. 117, pp. 40-52, 2018.

Area 4

• M. Herty, G. Puppo, G. Visconti. From kinetic to macroscopic models and back, Mathematical Descriptions of Traffic Flow: Micro, Macro and Kinetic Models 12, 17, Springer Nature, 2021;

• L. Pareschi, M. Zanella. Monte Carlo stochastic Galerkin methods for the Boltzmann equation with uncertainties: space-homogeneous case. Journal of Computational Physics, vol. 423, art. 109822, 2020;

• W. Boscheri, L. Pareschi. High order pressure-based semi-implicit IMEX schemes for the 3D Navier-Stokes equations at all Mach numbers. Journal of Computational Physics, vol. 434, art. 110206, 2020;

• W. Boscheri, G. Dimarco. High order central WENO-Implicit-Explicit Runge Kutta schemes for the BGK model on general polygonal meshes. Journal of Computational Physics, vol. 422, art. 109766, 2020;

• G. Albi, G. Dimarco, L. Pareschi. Implicit-explicit multistep methods for hyperbolic systems with multiscale relaxation. SIAM Journal on Scientific Computing, vol. 42, pp. A2402-A2435, 2020;

• W. Boscheri. A space-time semi-Lagrangian advection scheme on staggered Voronoi meshes applied to free surface flows. Computers & Fluids, vol. 202, art. 104503, 2020;

• E. Abbate, A. Iollo, G. Puppo. An Asymptotic-Preserving All-Speed Scheme for Fluid Dynamics and Nonlinear Elasticity. SIAM Journal on Scientific Computing, Vol. 41, pp. A2850-A2879, 2019;

• C. Klingenberg, G. Puppo, M. Semplice. Arbitrary order finite volume well-balanced schemes for the Euler equations with gravity. SIAM Journal on Scientific Computing, Vol. 41, pp. A695-A721, 2019;

• G. Dimarco, L. Pareschi. Multiscale control variate strategies for uncertainty quantification in kinetic equations. Journal of Computational Physics, vol. 388, pp. 63-89, 2019;

• J. A. Carrillo, L. Pareschi, M. Zanella. Particle based gPC methods for mean-field models of swarming with uncertainty. Communications in Computational Physics, vol. 25, pp. 508-531, 2019;

• G. Dimarco, R. Loubère, J. Narski, T. Rey. An efficient numerical method for solving the Boltzmann equation in multidimensions. Journal of Computational Physics, vol. 353, pp. 46-81, 2018;

• L. Pareschi, M. Zanella. Structure preserving schemes for nonlinear Fokker-Planck equations and applications. Journal of Scientific Computing, vol. 74, pp. 1575-1600, 2018;

• F. Bernard, A. Iollo, G. Puppo. BGK Polyatomic Model for Rarefied Flows. Journal of Scientific Computing,  Vol. 78, pp. 1893-1916, 2018;
• I. Cravero, G. Puppo, M. Semplice, G. Visconti. CWENO: uniformly accurate reconstructions for balance laws. Mathematics of Computation, Vol. 87, pp. 1689-1719, 2018.