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mathematics for sustainable development

scientific coordinator: Luca Formaggia

 

The main goals for this topic are the development of mathematical models and numerical methods with applications to biomedicine (e.g., precision medicine, mathematical oncology, neurosciences) and for the sustainable use of the subsoil and mitigation of the effects of human activities (e.g., CO2 sequestration, geothermal reservoirs), as well as the implementation and analysis of scientific machine learning algorithms.

 

 

Publications

2024

  • Arostica R. et al. A software benchmark for cardiac elastodynamics. 2025. Computer Methods in Applied Mechanics and Engineering, 435: 117485, https://doi.org/10.1016/j.cma.2024.117485
  • Ieva, F., Michael Ronzulli, M., Paganoni, A.M., 2025. A Spearman dependence matrix for multivariate functional data. Journal of Nonparametric Statistics, 82-104, https://doi.org/10.1080/10485252.2024.2353615
  • Spreafico, M., Ieva, F., Fiocco, M., 2024. Causal effect of chemotherapy received dose intensity on survival outcome: a retrospective study in osteosarcoma. BMC Med Res Methodol 24, 296 https://doi.org/10.1186/s12874-024-02416-x
  • Cavazzutti, M., Arnone, E., Ferraccioli, F., Finos, L., Sangalli, L., Efficient Parametric Tests in Semiparametric Regression with Differential Regularization, 2025, Pollice, A., Mariani, P. (eds) Methodological and Applied Statistics and Demography III. SIS 2024. Italian Statistical Society Series on Advances in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-031-64431-3_61
  • Corda, A., Pagani, S., Vergara, C., Influence of acute myocardial ischemia on arrhythmogenesis: a computational study, 2025, preprint, https://www.medrxiv.org/content/10.1101/2024.11.20.24317476v1
  • D. Nolte, A. Brown, A. Gebauer, E. Karabelas, J. Jilberto, M. Salvador, M. Bucelli, R. Piersanti, K. Osouli, C. Augustin, L. Shi, H. Finsberg, M. Pfaller, M. Hirschvogel, P. Africa, M. Gsell, A. Marsden, D. Nordsletten, F. Regazzoni, G. Plank, J. Sundnes, L. Dede’, M. Peirlinck, V. Vedula, W. Wall, C. Bertoglio, A software benchmark for cardiac elastodynamics, 2025, Computer Methods in Applied Mechanics and Engineering, 435: 117485, https://doi.org/10.1016/j.cma.2024.117485
  • Tomasetto, M., Arnone, E., Sangalli, L.M., "Modeling Anisotropy and Non-Stationarity Through Physics-Informed Spatial Regression", Environmetrics 35, e2889, 2024;
  • F. Lespagnol, C. Grandmont, P. Zunino, M.A. Fernández, "A mixed-dimensional formulation for the simulation of slender structures immersed in an incompressible flow", Comput. Methods Appl. Mech. Eng. 432, 117316, 2024;
  • M. Boulakia, C. Grandmont, F. Lespagnol, P. Zunino, "Mathematical and numerical analysis of reduced order interface conditions and augmented finite elements for mixed dimensional problems", Comput. Math. Appl. 175, 536–569, 2024;
  • E. Ballini, L. Formaggia, A. Fumagalli, A. Scotti, P. Zunino, "Application of deep learning reduced-order modeling for single-phase flow in faulted porous media", Comput. Geosci. 28, 1279–1303, 2024;
  • P. Vitullo, N.R. Franco, P. Zunino, "Deep learning enhanced cost-aware multi-fidelity uncertainty quantification of a computational model for radiotherapy", Found. Data Sci. 7, 386–417, 2024;
  • N. Dimola, M. Kuchta, K.A. Mardal, P. Zunino, "Robust Preconditioning of Mixed-Dimensional PDEs on 3d-1d Domains Coupled with Lagrange Multipliers", iA. Linninger, K.A. Mardal, P. Zunino (eds), "Quantitative approaches to microcirculation: mathematical models, computational methods and data analysis", SEMA SIMAI Springer Series 36, 137–171, 2024;
  • L. Possenti, A. Gallo, P. Vitullo, A. Cicchetti, T. Rancati, M.L. Costantino, P. Zunino, "A computational model of the tumor microenvironment applied to fractioned radiotherapy", in A. Linninger, K.A. Mardal, P. Zunino (eds), "Quantitative approaches to microcirculation: mathematical models, computational methods and data analysis", SEMA SIMAI Springer Series 36, 23–47, 2024;
  • L. Possenti, P. Vitullo, A. Cicchetti, P. Zunino, T. Rancati, "Modeling hypoxia-induced radiation resistance and the impact of radiation sources", Comput. Biol. Med. 173, 108334, 2024;
  • A. Fumagalli, L. Panzeri, L. Formaggia, A. Scotti, D. Arosio, "A mixed-dimensional model for direct current simulations in the presence of a thin high-resistivity liner", Int. J. Numer. Methods Eng. 125,  e7407, 2024;
  • L. Ghilotti, M. Beraha, A. Guglielmi, "Bayesian clustering of high-dimensional data via latent repulsive mixtures", Biometrika, asae059, 2024;
  • C.A. Tentori, C. Gregorio, et al, "Clinical and Genomic-Based Decision Support System to Define the Optimal Timing of Allogeneic Hematopoietic Stem-Cell Transplantation in Patients With Myelodysplastic Syndromes", J. Clin. Oncol. 42, 2024;
  • V. Torri, M. Ercolanoni, F. Bortolan, O. Leoni, F. Ieva, "A NLP-based semi-automatic identification system for delays in follow-up examinations: an Italian case study on clinical referrals", BMC Med. Inform. Decis. Mak. 24, 107, 2024;
  • B. Guindani, D. Ardagna, A. Guglielmi, R. Rocco, G. Palermo, "Integrating Bayesian Optimization and Machine Learning for the Optimal Configuration of Cloud Systems", IEEE Trans. Cloud Comp.12, 277-294, 2024;
  • P.F. Antonietti, M. Botti, A. Cancrini, I. Mazzieri, "A polytopal Discontinuous Galerkin Method for the pseudo-stress formulation of the unsteady Stokes problem", preprint arXiv:2408.08760 [math.NA], 2024;