Research & Publications

Research

Scientific Interest

  • Anisotropic mesh adaptation
    − P. Africa, C. De Falco, N. Ferro, L. Formaggia, S. Micheletti (Politecnico di Milano);
    − G. Alaimo, M. Carraturo, S. Marconi (Università degli Studi di Pavia);
    − S. Beretta, S. Foletti, M. Gavazzoni (Politecnico di Milano);
    − A. Cangiani (University of Nottingham);
    − C. Ciancarelli, L. Soli (Thales Alenia Space Italia, Gorgonzola – Roma);
    − F. Clerici (Inria Saclay Île-De-France);
    − M. Giacomini (CIMNE, Universitat Politècnica de Catalunya, Barcelona);
    − M. Lupo Pasini (Oak Ridge National Laboratory);
    − A. Mauri (Micron Technology);
    − C. Nardoni (Institut de Recherche Technologique SystemX);
    − E. Negrello (Policlinico San Matteo di Pavia);
    − T. Villa (Politecnico di Milano).
  • Model reduction and model adaptation
    − F. Ballarin, G. Rozza (SISSA, Trieste);
    − M.G. Carlino, A. Iollo (University of Bordeaux, Inria Bordeaux Sud-Ouest);
    − M. Lupo Pasini (Oak Ridge National Laboratory);
    − K. Calò, D. Gallo, V. Mazzi, U. Morbiducci (Politecnico di Torino);
    − P. Zunino (Politecnico di Milano).
  • Advanced numerical methods and mathematical models for smart farming
    − L. Bascetta, M. Matteucci (Politecnico di Milano);
    − C. Ciancarelli, L. Soli (Thales Alenia Space Italia, Gorgonzola – Roma);
    − N. Ferro (Politecnico di Milano).
  • Advanced techniques for the design of innovative cellular materials
    − D. Bianchi, R. Ferrante, M. Mannisi (Medere S.r.l, Roma);
    − D. Carbonaro, C. Ciastra, D. Gallo, U. Morbiducci (Politecnico di Torino);
    − N. Ferro (Politecnico di Milano);
    − S. Foletti, M. Gavazzoni (Politecnico di Milano);
    − M. Matteucci (Politecnico di Milano);
    − F. Mezzadri (Università degli Studi di Modena e Reggio Emilia).
  • Modeling of free-surface flows and of solute transport in porous media
    − G. Conni (KU Leuven);
    − M. Icardi (University of Nottingham);
    − G.M. Porta (Politecnico di Milano);
    − S. Piccardo (CERMICS, Paris – LaCàN Universitat Politècnica de Catalunya, Barcelona).
  • Statistical-numerical analysis of high dimensional functional data
    − L. Sangalli (Politecnico di Milano).
  • Compressed sensing
    − S. Brugiapaglia (Concordia University, Montréal);
    − S. Micheletti (Politecnico di Milano);
    − F. Nobile (EPFL, Lausanne).
  • Bayesian computing
    − D. Calvetti, E. Somersalo, A. Bocchinfuso (Case Western Reserve University, Cleveland).

Visiting Periods

  • Muenster University, Germany (3 – 5 November, 2009).
  • Emory University, Atlanta, USA (14 – 23 February, 2012).
  • CEMEF/Ecole des Mines de Paris, Sophia Antipolis, France (20 – 22 September, 2014).
  • EPFL, Lausanne, Switzerland (6 – 7 November, 2014).
  • WIAS, Berlin, Germany (2 –5 March, 2015).
  • Emory University, Atlanta, USA (20 – 30 November, 2015).
  • BCAM, Bilbao, Spain (22 – 25 February, 2016).
  • Ecole Centrale de Nantes, France (2 – 3 March, 2016).
  • Emory University, Atlanta, USA (29 April – 6 May, 2016).
  • Emory University, Atlanta, USA (24 November – 9 December, 2016).
  • UPC, Barcelona, Spain (8 – 9 February, 2017).
  • Emory University, Atlanta, USA (20 February – 3 March, 2017).
  • SISSA, Trieste, Italy (19 – 21 July, 2017).
  • Emory University, Atlanta, USA (31 August – 12 September, 2017).
  • Emory University, Atlanta, USA (15 January – 10 May, 2018).
  • Virginia Tech, Blacksburg, USA (4 – 6 November, 2019).
  • Case Western Reserve University, Cleveland, USA (7 – 9 November, 2019).

Publications

Peer-Reviewd Journals

  1. C. Dagnino, S. Perotto, E. Santi. Convergence of rules based on nodal splines for the numerical evaluation of
    certain 2D Cauchy principal value integrals.     J. Comput. Appl. Math., 89 (1998), no.2, 225-235.
  2. M. Grasselli, S. Perotto, F. Saleri. Space-time finite elements for Boussinesq equations. East-West J. Numer. Math., 7 (1999), no.4, 283-306.
  3. S. Perotto, F. Saleri. Adaptive finite element methods for Boussinesq equations. Numer. Methods Partial Differential Equations, 16 (2000), no.2, 214-236.
  4. L. Formaggia, S. Perotto. New anisotropic a priori error estimates. Numer. Math., 89 (2001), 641-667.
  5. L. Formaggia, S. Perotto, P. Zunino. An anisotropic a-posteriori error estimate for a convection-diffusion problem. Comput. Visual. Sci., 4 (2001), no.2, 99-104.
  6. L. Formaggia, S. Perotto. Anisotropic error estimates for elliptic problems. Numer. Math., 94 (2003), 67-92.
  7. S. Micheletti, S. Perotto, M. Picasso. Stabilized finite elements on anisotropic meshes: a priori error estimates for the advection-diffusion and the Stokes problems. SIAM J. Numer. Anal., 41 (2003), no.3, 1131-1162.
  8. L. Formaggia, S. Micheletti, S. Perotto. Anisotropic mesh adaptation in Computational Fluid Dynamics: application to the advection-diffusion-reaction and the Stokes problems. Appl. Numer. Math., 51 (2004), no.4, 511-533.
  9. S. Perotto. Anisotropic mesh adaption: application to Computational Fluid Dynamics. Bollettino dell’Unione Matematica Italiana, Sezione B-Articoli di Ricerca Matematica, 8-B (2005), 145-165, Zanichelli Editore S.p.A.
  10. E. Miglio, S. Perotto, F. Saleri. Model coupling techniques for free-surface flow problems. Part I. Nonlinear Anal., 63 (2005), no.5-7, 1885-1896.
  11. E. Miglio, S. Perotto, F. Saleri. Model coupling techniques for free-surface flow problems. Part II. Nonlinear Anal., 63 (2005), no.5-7, 1897-1908.
  12. S. Micheletti, S. Perotto. Reliability and efficiency of an anisotropic Zienkiewicz-Zhu error estimator. Comput. Methods Appl. Mech. Engrg., 195 (2006), no.9-12, 799-835.
  13. C.L. Bottasso, G. Maisano, S. Micheletti, S. Perotto. On some new recovery based a posteriori error estimators. Comput. Methods Appl. Mech. Engrg., 195 (2006), no.37-40, 4794-4815.
  14. S. Perotto. Adaptive modeling for free-surface flows. M2AN Math. Model. Numer. Anal., 40 (2006), no.3, 469-499.
  15. S. Micheletti, S. Perotto, M. Verani. Uzawa-based adaptive methods for linear output functionals. IMA J. 7 Numer. Anal., 28 (2008), no.3, 619-646.
  16. L. Dedè, S. Micheletti, S. Perotto. Anisotropic error control for environmental applications. Appl. Numer. Math., 58 (2008), no.9, 1320-1339.
  17. S. Micheletti, S. Perotto. Output functional control for nonlinear equations driven by anisotropic mesh adaption. The Navier-Stokes equations. SIAM J. Sci. Comput., 30 (2008), no.6, 2817-2854.
  18. S. Micheletti, S. Perotto. Anisotropic mesh adaption for time-dependent problems. Internat. J. Numer. Methods Fluids, 58 (2008), 1009-1015.
  19. S. Micheletti, S. Perotto. Space-time adaptation for purely diffusive problems in an anisotropic framework. Int. J. Numer. Anal. Model., 7 (2010), no.1, 125-155.
  20. S. Perotto, A. Ern, A. Veneziani. Hierarchical local model reduction for elliptic problems: a domain decomposition approach. Multiscale Model. Simul., 8 (2010), no.4, 1102-1127.
  21. P.E. Farrell, S. Micheletti, S. Perotto. A recovery-based error estimator for anisotropic mesh adaptation in CFD. Bol. Soc. Esp. Mat. Apl., 50 (2010), 115-138.
  22. P.E. Farrell, S. Micheletti, S. Perotto. An anisotropic Zienkiewicz-Zhu type error estimator for 3D applications. Int. J. Numer. Methods Engng, 85 (2011), 671-692.
  23. M. Lefebvre, S. Perotto. A semi-Markov process with an inverse Gaussian distribution as sojourn time. Appl. Math. Model., 35 (2011), 4603-4610.
  24. S. Micheletti, S. Perotto. The effect of anisotropic mesh adaptation on PDE-constrained optimal control problems. SIAM J. Control. Optim., 49 (2011), no.4, 1793-1828.
  25. G.M. Porta, S. Perotto, F. Ballio. Anisotropic mesh adaptation driven by a recovery-based error estimator for shallow water flow modeling. Internat. J. Numer. Methods Fluids, 70 (2012), no.3, 269-299.
  26. G.M. Porta, S. Perotto, F. Ballio. A space-time adaptation scheme for unsteady shallow water problems. Math. Comput. Simulation, 82 (2012), 2929-2950.
  27. S. Micheletti, S. Perotto, F. David. Model adaptation enriched with an anisotropic mesh spacing for nonlinear equations: application to environmental and CFD problems. Numer. Math. Theor. Meth. Appl., 6 (2013), no. 3, 447-478.
  28. S. Perotto, A. Veneziani. Coupled model and grid adaptivity in hierarchical reduction of elliptic problems. J. Sci. Comput., 60 (2014), no. 3, 505-536.
  29. F. Dassi, S. Perotto, L. Formaggia, P. Ruffo. Efficient geometric reconstruction of complex geological structures. Math. Comput. Simulation, 106 (2014), 163-184.
  30. T. Taddei, S. Perotto, A. Quarteroni. Reduced basis techniques for nonlinear conservation laws. M2AN Math. Model. Numer. Anal., 49 (2015), no. 3, 787-814.
  31. F. Dassi, B. Ettinger, S. Perotto, L.M. Sangalli. A mesh simplification strategy for a spatial regression analysis over the cortical surface of the brain. Appl. Numer. Math., 90 (2015), 111-131.
  32. B. Esfandiar, G.M. Porta, S. Perotto, A. Guadagnini. Impact of space-time mesh adaptation on solute transport modeling in porous media. Water Resour. Res., 51 (2015), no. 2, 1315-1332.
  33. M. Artina, M. Fornasier, S. Micheletti, S. Perotto. Anisotropic mesh adaptation for crack detection in brittle materials. SIAM J. Sci. Comput., 37 (2015), no. 4, B633-B659.
  34. S. Brugiapaglia, S. Micheletti, S. Perotto. Compressed solving: a numerical approximation technique for elliptic PDEs based on compressed sensing. Comput. Math. Appl., 70 (2015), 1306-1335.
  35. F. Dassi, S. Perotto, L. Formaggia. A priori anisotropic mesh adaptation on implicitly defined surfaces. SIAM J. Sci. Comput., 37 (2015), no. 6, A2758-A2782.
  36. S. Perotto, A. Zilio. Space-time adaptive hierarchical model reduction for parabolic equations. Adv. Model. and Simul. in Eng. Sci., 2:25 (2015).
  37. B. Ettinger, S. Perotto, L.M. Sangalli. Spatial regression models over two-dimensional manifolds. Biometrika, 103 (2016), no. 1, 71-88.
  38. S. Perotto, A. Reali, P. Rusconi, A. Veneziani. HIGAMod: a Hierarchical IsoGeometric Approach for MODel reduction in curved pipes. Comput. & Fluids, 142 (2017), 21-29.
  39. M. Signorini, S. Micheletti, S. Perotto. CMFWI: Coupled Multiscenario Full Waveform. Inverse Probl. Sci. Eng., 25 (2017), no. 7, 939-964.
  40. F. Dassi, S. Perotto, H. Si, T. Streckenbach. A priori anisotropic mesh adaptation driven by a higher 8-dimensional embedding. Comput.-Aided Des, 85 (2017), 111-122.
  41. A. Crivellaro, S. Perotto, S. Zonca. Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques. Appl. Numer. Math., 113 (2017), 93-108.
  42. S. Brugiapaglia, F. Nobile, S. Micheletti, S. Perotto. A theoretical study of compressed solving for advection-diffusion-reaction problems. Math. Comp., 87 (2018), no. 309, 1-38.
  43. C.B. Rizzo, F.P.J. de Barros, S. Perotto, L. Oldani, A. Guadagnini. Adaptive POD model reduction for solute transport in heterogeneous porous media. Comput. Geosci., 22 (2018), no. 1, 297-308.
  44. S. Micheletti, S. Perotto, M. Signorini. Anisotropic mesh adaptation for the generalized Ambrosio-Tortorelli functional with application to brittle fracture. Comput. Math. Appl., 75 (2018), 2134-2152.
  45. E. Beretta, S. Micheletti, S. Perotto, M. Santacesaria. Reconstruction of a piecewise constant conductivity on a polygonal partition via shape optimization in EIT. J. Comput. Phys., 353 (2018), 264-280.
  46. S. Guzzetti, S. Perotto, A. Veneziani. Hierarchical model reduction for incompressible fluids in pipes. Internat. J. Numer. Methods Engrg., 114 (2018), no. 5, 469-500.
  47. M. Aletti, S. Perotto, A. Veneziani. HiMod reduction of advection-diffusion-reaction problems with general boundary conditions. J. Sci. Comput., 76 (2018), no. 1, 89-119.
  48. N. Ferro, S. Micheletti, S. Perotto. Anisotropic mesh adaptation for crack propagation induced by a thermal shock in 2D. Comput. Methods Appl. Mech. Engrg., 331 (2018), 138-158.
  49. V. Bacchelli, S. Micheletti, S. Perotto, D. Pierotti. Parameter identification for the linear wave equation with Robin boundary condition. J. Inverse Ill-Posed Probl., 27 (2019), no. 1, 25-41.
  50. F. Ballarin, A. D’Amario, S. Perotto, G. Rozza. A POD-selective inverse distance weighting method for fast parametrized shape morphing. Internat. J. Numer. Methods Engrg., 117 (2019), no. 8, 860-884.
  51. N. Ferro, S. Micheletti, S. Perotto. POD-assisted strategies for structural topology optimization. Comput. Math. Appl., 77 (2019), no. 10, 2804-2820.
  52. S. Micheletti, S. Perotto, L. Soli. Topology optimization driven by anisotropic mesh adaptation: towards a free-form design. Comput. & Structures, 214 (2019), 60-72.
  53. A.S. Chiappa, S. Micheletti, R. Peli, S. Perotto. Mesh adaptation-aided image segmentation. Commun. Nonlinear Sci. Numer. Simulat. 74 (2019), 147-166.
  54. Y.A. Brandes Costa Barbosa, S. Perotto. Hierarchically reduced models for the Stokes problem in patientspecific artery segments. Int. J. Comput. Fluid Dyn. 34 (2020), no. 2, 160-171.
  55. N. Ferro, S. Micheletti, S. Perotto. Compliance–stress constrained mass minimization for topology optimization on anisotropic meshes. SN Applied Sciences 2: 1196 (2020).
  56. N. Ferro, S. Micheletti, S. Perotto. An optimization algorithm for automatic structural design. Comput. Methods Appl. Mech. Engrg. 372 (2020), 113335.
  57. A. Barone, M.G. Carlino, A. Gizzi, S. Perotto, A. Veneziani. Efficient estimation of cardiac conductivities: a Proper Generalized Decomposition approach. J. Comput. Phys. 423 (2020), 109810.
  58. D. Calvetti, A. Cosmo, S. Perotto, E. Somersalo. Bayesian mesh adaptation for estimating distributed parameters. SIAM J. Sci. Comput. 42 (2020), no. 6, A3878-A3906.
  59. F. Clerici, N. Ferro, S. Marconi, S. Micheletti, E. Negrello, S. Perotto. Anisotropic adapted meshes for image segmentation: application to 3D medical data. SIAM J. Imaging Sci. 13 (2020), no. 4, 2189-2212.
  60. S. Almi, S. Belz, S. Micheletti, S. Perotto. A dimension-reduction model for brittle fractures on thin shells with mesh adaptivity. Math. Models Methods Appl. Sci. 31 (2021), no. 1, 37-81.
  61. M. Zancanaro, F. Ballarin, S. Perotto, G. Rozza. Hierarchical model reduction techniques for flow modeling in a parametrized setting. Multiscale Model. Simul. 19 (2021), no. 1, 267-293.
  62. S. Brugiapaglia, F. Nobile, S. Micheletti, S. Perotto. Wavelet-Fourier CORSING techniques for multidimensional advection-diffusion-reaction equations. IMA J. Numer. Anal. 41 (2021), 2744-2781.
  63. M. Lupo Pasini, V. Gabbi, J. Yin, S. Perotto, N. Laanait. Scalable balanced training of conditional generative adversarial neural networks on image data. J. Supercomput. 77 (2021), no. 11, 13358-13384.
  64. A. Pasquale, A. Ammar, A. Falcó, S. Perotto, E. Cueto, J.-L. Duval, F. Chinesta. A separated representation involving multiple time scales within the Proper Generalized Decomposition framework. Adv. Model. and Simul. in Eng. Sci., 8:26 (2021).
  65. F. Dassi, J.M. Kroos, L. Gerardo-Giorda, S. Perotto. A denoising tool for the reconstruction of cortical 9 geometries from MRI. Math. Comput. Simulation 191 (2022), 14-32.
  66. N. Ferro, S. Perotto, A. Cangiani. An anisotropic recovery-based error estimator for adaptive discontinuous Galerkin methods. J. Sci. Comput. 90: 45 (2022).
  67. M. Lupo Pasini, S. Perotto. Hierarchical model reduction driven by a Proper Orthogonal Decomposition for parametrized advection-diffusion-reaction problems. Electron. Trans. Numer. Anal. 55 (2022), 187-212.
  68. G.G. Gentili, M. Khosronejad, G. Bernasconi, S. Perotto, S. Micheletti. Efficient modeling of multimode guided acoustic wave propagation in deformed pipelines by hierarchical model reduction. Appl. Numer. Math. 173 (2022), 329-344.
  69. N. Ferro, S. Perotto, D. Bianchi, R. Ferrante, M. Mannisi. Design of cellular materials for multiscale topology optimization: application to patient-specific orthopaedic devices. Struct. Multidiscip. Optim. 65:79 (2022).
  70. M. Gavazzoni, N. Ferro, S. Perotto, S. Foletti. Multi-physics inverse homogenization for the design of innovative cellular materials: application to thermo-elastic problems. Math. Comput. Appl. 27:15 (2022).
  71. F. Vaccaro, S. Brivio, S. Perotto, A.G. Mauri, S. Spiga. Physics-based compact modelling of the analog dynamics of HfOx resistive memories. In press on Neuromorph. Comput. Eng.
  72. M. Giacomini, S. Perotto. Anisotropic mesh adaptation for region-based segmentation accounting for image spatial information. Accepted for publication in Comput. Math. Appl. (2022).

Peer-Reviewed Journals (submitted)

  1. L. Ponti, S. Perotto, L.M. Sangalli. PDE-regularized smoothing method for space-time data over manifolds
    with application to medical data.     MOX Report no. 76/2021, Dipartimento di Matematica, Politecnico di Milano.
  2. M. Lupo Pasini, S. Perotto. Hierarchical model reduction driven by machine learning for parametric advection-diffusion-reaction problems in the presence of noisy data. MOX Report no. 19/2022, Dipartimento di Matematica, Politecnico di Milano (arXiv:2204.00538).
  3. S. Perotto, G. Bellini, F. Ballarin, K. Calò, V. Mazzi, U. Morbiducci. Isogeometric Hierarchical Model Reduction for advection-diffusion process simulation in microchannels. MOX Report no. 35/2022, Dipartimento di Matematica, Politecnico di Milano (arXiv:2205.08127).
  4. N. Ferro, S. Perotto, M. Gavazzoni. A new fluid-based strategy for the connection of non-matching lattice materials. MOX Report no. 39/2022, Dipartimento di Matematica, Politecnico di Milano (arXiv:2206.00994).
  5. F. Gatti, M. Fois, C. de Falco, S. Perotto, L. Formaggia. Parallel simulations for fast-moving landslides: space-time mesh adaptation and sharp tracking of the wetting front. MOX Report no. 42/2022, Dipartimento di Matematica, Politecnico di Milano.

Peer-Reviewed Proceedings

  1. C. Dagnino, S. Perotto, E. Santi. Product formulas based on spline approximation for the numerical evaluation of certain 2D CPV integrals. In Approximation and Optimization, Vol. I, Transilvania, Cluj-Napoca (1997), 241-250.
  2. S. Micheletti, S. Perotto. An anisotropic recovery-based a posteriori error estimator. In Numerical Mathematics and Advanced Applications, Springer-Verlag Italia, F. Brezzi, A. Buffa, S. Corsaro, A. Murli Eds. (2003), 731-741.
  3. E. Miglio, S. Perotto, F. Saleri. A multiphysics strategy for free surface flows. In Domain Decomposition Methods in Science and Engineering. Series: Lect. Notes Comput. Sci. Eng., Vol. 40, Springer-Verlag Berlin Heidelberg, R. Kornhuber, R. Hoppe, J. Périaux, O. Pironneau, O. Widlund, J. Xu Eds. (2005), 395-402.
  4. S. Micheletti, S. Perotto. Anisotropic mesh adaptivity in CFD. In Adaptive Mesh Refinement-Theory and Applications. Series: Lect. Notes Comput. Sci. Eng., Vol. 41, Springer Berlin Heidelberg, T. Plewa, T. Linde, V.G. Weirs Eds. (2005), 171-182.
  5. S. Micheletti, S. Perotto, F. Schiavo. Modelling heat exchangers by the finite element method with grid adaption in Modelica. In Proceedings of the 4th International Modelica Conference, Amburgo, March 7-8, 2005; 10 G.Schmitz Ed. (2005), 219-228.
  6. S. Micheletti, S. Perotto. Anisotropic mesh adaptivity via a dual-based a posteriori error estimation for semiconductors. In Scientific Computing in Electrical Engineering. Series: Mathematics in Industry, Vol. 9, Springer-Verlag Berlin Heidelberg, A.M. Anile, G. Alì, G. Mascali Eds. (2006), 369-375.
  7. S. Micheletti, S. Perotto. Space-time adaption for advection-diffusion-reaction problems on anisotropic meshes. In Numerical Mathematics and Advanced Applications, Springer-Verlag Berlin Heidelberg, K. Kunisch, G. Of, O. Steinbach Eds. (2008), 49-56.
  8. A. Ern, S. Perotto, A. Veneziani. Hierarchical model reduction for advection-diffusion-reaction problems. In Numerical Mathematics and Advanced Applications, Springer-Verlag Berlin Heidelberg, K. Kunisch, G. Of, O. Steinbach Eds. (2008), 703-710.
  9. S. Micheletti, S. Perotto. Anisotropic adaptation via a Zienkiewicz-Zhu error estimator for 2D elliptic problems. In Numerical Mathematics and Advanced Applications, Springer-Verlag Berlin Heidelberg, G. Kreiss, P. Lotstedt, A. Malqvist, M. Neytcheva Eds. (2010), 645-653.
  10. S. Micheletti, S. Perotto. Anisotropic recovery-based a posteriori error estimators for advection-diffusionreaction problems. In Numerical Mathematics and Advanced Applications, Springer-Verlag, Berlin Heidelberg, A. Cangiani, R.L. Davidchack, E. Georgoulis, A.N. Gorban, J. Levesley, M.V. Tretyakov Eds. (2013), 43-51.
  11. S. Perotto, A. Zilio. Hierarchical model reduction: three different approaches. In Numerical Mathematics and Advanced Applications, Springer-Verlag Berlin Heidelberg, A. Cangiani, R.L. Davidchack, E. Georgoulis, A.N. Gorban, J. Levesley, M.V. Tretyakov Eds. (2013), 851-859.
  12. L. Mauri, S. Perotto, A. Veneziani. Adaptive geometrical multiscale modeling for hydrodynamic problems. In Numerical Mathematics and Advanced Applications, Springer-Verlag Berlin Heidelberg, A. Cangiani, R.L. Davidchack, E. Georgoulis, A.N. Gorban, J. Levesley, M.V. Tretyakov Eds. (2013), 723-730.
  13. S. Perotto. Hierarchical model (Hi-Mod) reduction in non-rectilinear domains. In Domain Decomposition Methods in Science and Engineering. Series: Lect. Notes Comput. Sci. Eng., Vol. 98, Springer Cham, J. Erhel, M. Gander, L. Halpern, G. Pichot, T. Sassi, O. Widlund Eds. (2014), 477-485.
  14. M. Artina, M. Fornasier, S. Micheletti, S. Perotto. Anisotropic adaptive meshes for brittle fractures: parameter sensitivity. In Numerical Mathematics and Advanced Applications. Series: Lect. Notes Comput. Sci. Eng., Vol. 103, Springer, A. Abdulle, S. Deparis, D. Kressner, F. Nobile, M. Picasso Eds. (2015), 293-302.
  15. M. Aletti, A. Bortolossi, S. Perotto, A. Veneziani. One-dimensional surrogate models for advection-diffusion problems. In Numerical Mathematics and Advanced Applications. Series: Lect. Notes Comput. Sci. Eng., Vol. 103, Springer, A. Abdulle, S. Deparis, D. Kressner, F. Nobile, M. Picasso Eds. (2015), 447-456.
  16. M. Fedele, E. Faggiano, L. Barbarotta, F. Cremonesi, L. Formaggia, S. Perotto. Semi-automatic three-dimensional vessel segmentation using a connected component localization of the region-scalable fitting energy. IEEE (2015), 72-77, 9th International Symposium on Image and Signal Processing and Analysis (ISPA).
  17. F. Dassi, H. Si, S. Perotto, T. Streckenbach. Anisotropic finite element mesh adaptation via higher dimensional embedding. Procedia Engineering, 124, (2015), 265-277.
  18. N. Ferro, S. Micheletti, S. Perotto. Density-based inverse homogenization with anisotropically adapted elements. In Numerical Methods for Flows. FEF 2017 Selected Contributions. Series: Lect. Notes Comput. Sci. Eng., Vol. 132, Springer Cham, A. Corsini, S. Perotto, G. Rozza, H. van Brummelen Eds. (2020), 211-221.
  19. S. Perotto, M.G. Carlino, F. Ballarin. Model reduction by separation of variables: a comparison between Hierarchical Model Reduction and Proper Generalized Decomposition. In Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018. Series: Lect. Notes Comput. Sci. Eng., Vol. 134, Springer Nature Switzerland, S.J. Sherwin, D. Moxey, J. Peirò, P.E. Vincent, C. Schwab Eds. (2020), 61-77.
  20. M. Lupo, M. Burcul, S. Reeve, M. Eisenbach, S. Perotto. Fast and accurate predictions of total energy for solid solution alloys with graph convolutional neural networks. In Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation. SMC 2021. Series: Communications in Computer and Information Science, Vol. 1512, Springer Nature Switzerland, J. Nichols, A.B. Maccabe, J. Nutaro, S. Pophale, P. Devineni, T. Ahearn, B. Verastegui Eds. (2022), 79-98.

Contributed Books

  1. B. Ettinger, T. Passerini, S. Perotto, L.M. Sangalli. Regression models for data distributed over non-planar 11 domains. In Complex Models and Computational Methods in Statistics. Series: Contributions to Statistics,
    Springer, Milano, M. Grigoletto, F. Lisi, S. Petrone Eds. (2013), 123-135.
  2. S. Perotto. A survey of hierarchical model (Hi-Mod) reduction methods for elliptic problems. In Numerical Simulations of Coupled Problems in Engineering. Series: Computational Methods in Applied Sciences, Vol. 33, Springer, S.R. Idelsohn Ed. (2014), 217-241.
  3. M. Artina, M. Fornasier, S. Micheletti, S. Perotto. The benefits of anisotropic mesh adaptation for brittle fractures under plane-strain conditions. In New Challenges in Grid Generation and Adaptivity for Scientific Computing. Series: SEMA SIMAI Springer, Vol. 5, Springer Cham, S. Perotto, L. Formaggia Eds. (2015), 43-67.
  4. B. Esfandiar, G.M. Porta, S. Perotto, A. Guadagnini. Anisotropic mesh and time step adaptivity for solute transport modeling in porous media. In New Challenges in Grid Generation and Adaptivity for Scientific Computing. Series: SEMA SIMAI Springer, Vol. 5, Springer Cham, S. Perotto, L. Formaggia Eds. (2015), 231-260.
  5. D. Baroli, C.M. Cova, S. Perotto, L. Sala, A. Veneziani. Hi-POD solution of parametrized fluid dynamics problems: preliminary results. In Model Reduction of Parametrized Systems. Series: MS&A Springer, P. Benner, M. Ohlberger, A.T. Patera, G. Rozza, K. Urban Eds. (2017), Chapter 15, 235-254.
  6. A.G. Mauri, B. Morini, S. Perotto, F. Sgallari. Grid generation and algebraic solvers. To appear in Springer Handbook of Semiconductor Devices. Springer, M. Rudan, R. Brunetti, S. Reggiani Eds. (2021), Chapter 38.

Conference Papers

  1. S. Perotto. A posteriori error estimates for Boussinesq equations. In Numerical Methods for Fluid Dynamics VI. M.J. Baines Ed., Oxford (1998), 451-457. Proceedings of ICFD, Conference on Numerical Methods for
    Fluid Dynamics.
  2. S. Perotto. Modelling nonlinear dispersive waves. In Proceedings of WASCOM 99, 10th Conference on Waves and Stability in Continuous Media. V. Ciancio, A. Donato, F. Oliveri, S. Rionero Eds., World Scientific, Singapore (2001), 371-381.
  3. S. Micheletti, S. Perotto. A theoretical design of the stability coefficients on anisotropic elements. In Proceedings of SIMAI 2002, VI Congresso Nazionale della Società Italiana di Matematica Applicata e Industriale.
  4. L. Formaggia, S. Micheletti, S. Perotto. Anisotropic mesh adaption with application to CFD problems. In Proceedings of WCCM V, Fifth World Congress on Computational Mechanics, 2002. H.A. Mang, F.G. Rammerstorfer, J. Eberhardsteiner (Eds).
  5. L. Formaggia, S. Micheletti, S. Perotto. Anisotropic mesh adaption for advection-diffusion-reaction problems. In Proceedings of IMACS/ISGG Workshop MASCOT02, 2nd Meeting on Applied Scientific Computing and Tools, 2002.
  6. E. Miglio, S. Perotto, F. Saleri. Multiphysics coupling strategy for free surface flows. In Proceedings of ADMOS 2003, the 1st International Conference on Adaptive Modelling and Simulation. N.E. Wiberg, P. Díez (Eds).
  7. E. Miglio, S. Perotto, F. Saleri. A coupling strategy for free surface flows. In Proceedings of ECCOMAS 2004, 4th European Congress on Computational Methods in Applied Sciences and Engineering. P. Neittaanmäki, T. Rossi, S. Korotov, E. Onate, J. Périaux, D. Knörzer (Eds).
  8. B. Ettinger, S. Perotto, L.M. Sangalli. Spatial smoothing over non-planar domains. In Proceedings of the 46th Scientific Meeting of the Italian Statistical Society, 2012. ISBN 978-88-6129-882-8, Cleup Eds.
  9. B. Ettinger, S. Perotto, L.M. Sangalli. Studying hemodynamic forces via spatial regression models over nonplanar domains. In Proceedings of the 47th Scientific Meeting of the Italian Statistical Society, 2013. Electronic Book: Advances in Latent Variables-Methods, Models and Applications, Eds. E. Brentari, M. Carpita, Vita e Pensiero, Milano. ISBN 978-88-343-2556-8.
  10. B. Ettinger, S. Perotto, L.M. Sangalli. A functional data analysis approach to modeling spatially distributed data across several non-planar domains. In Proceedings of S.Co.2013, Complex Data Modeling and Computationally Intensive Statistical Methods for Estimation and Prediction, 2013. ISBN 9788864930190.
  11. E. Faggiano, T. Lorenzi, S. Perotto. TV-H1 variational inpainting applied to metal artifact reduction in CT 12 images. In Proceedings of VIPIMAGE 2013 – Computational Vision and Medical Image Processing IV, Taylor & Francis Group, London. Joao Manuel R. S. Tavares and R. M. Natal Jorge Eds. (2014), Chapter 47, 277-282.
  12. D. di Cristofaro, C. Galimberti, D. Bianchi, R. Ferrante, N. Ferro, M. Mannisi, S. Perotto. Adaptive topology optimization for innovative 3D printed metamaterials. In: Proceedings of WCCM – ECCOMAS 2020, Volume 1200 – Modeling and Analysis of Real World and Industry Applications Conference (DOI: 10.23967/wccm-eccomas.2020.049).

Editorial Activity

  1. Member of the editorial board of the Electronic Transactions on Numerical Analysis (ETNA) journal (2018-present);
  2. Member of the editorial board of the Mathematical and Computational Applications (MCA) journal (2020- present);
  3. Member of the editorial board of the International Journal of Computational Fluid Dynamics (JCFD) journal (2021-present);
  4. Editor of the volume New Challenges in Grid Generation and Adaptivity for Scientific Computing. Series: SEMA SIMAI Springer, Vol. 5, Springer Cham 2015 (editorship joint with L. Formaggia);
  5. Guest editor of the special issue on Model Reduction. J. Sci. Comput. 81 (2019), no. 1 (editorship joint with T. Lelièvre, G. Rozza, D.A. Di Pietro, A. Ern, L. Formaggia);
  6. Guest editor of the special issue for the 19th International Conference on Finite Elements in Flow Problems, Rome, April 5-7, 2017. Comput. & Fluids 179 (2019) (editorship joint with H. van Brummelen, A. Corsini, G. Rozza);
  7. Editor of the volume Numerical Methods for Flows. FEF 2017 Selected Contributions. Series: Lect. Notes Comput. Sci. Eng. Vol. 132, Springer Cham 2020 (editorship joint with H. van Brummelen, A. Corsini, G. Rozza);
  8. Guest editor of the special issue on Reduced Order Models in CFD. Int. J. Comput. Fluid Dyn. 34 (2020), no. 2 (editorship joint with G. Rozza);
  9. Editor of the volume Mesh Generation and Adaptation: Cutting-Edge Techniques. Series: SEMA SIMAI Springer, Vol. 30, Springer Nature Switzerland AG 2022 (editorship joint with R. Sevilla, K. Morgan);
  10. Guest editor of the special issue on Computational Methods for Coupled Problems in Science and Engineering. Mathematical and Computational Applications (editorship joint with A. Larese, G. Rozza).