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. Parametric POD-Galerkin Model Order Reduction for Unsteady-State Heat Transfer Problems. Communications in Computational Physics [Internet]. 2019 ;27:1–32. Available from: https://arxiv.org/abs/1808.05175
. POD-Galerkin reduced order methods for CFD using Finite Volume Discretisation: vortex shedding around a circular cylinder. Communications in Applied and Industrial Mathematics. 2017 ;8:210-236.
. A POD-Galerkin reduced order model for a LES filtering approach. Journal of Computational Physics [Internet]. 2021 ;436. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102138957&doi=10.1016%2fj.jcp.2021.110260&partnerID=40&md5=73115708267e80754f343561c26f4744
. A POD-Galerkin reduced order model for the Navier–Stokes equations in stream function-vorticity formulation. [Internet]. 2022 :105536. Available from: https://www.sciencedirect.com/science/article/pii/S0045793022001645
. A POD-Galerkin reduced order model of a turbulent convective buoyant flow of sodium over a backward-facing step. Applied Mathematical Modelling. 2021 ;89:486-503.
. POD-Galerkin Reduced Order Model of the Boussinesq Approximation for Buoyancy-Driven Enclosed Flows. In: International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019. ; 2019.
. A POD-selective inverse distance weighting method for fast parametrized shape morphing. International Journal for Numerical Methods in Engineering [Internet]. 2019 ;117:860-884. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056396233&doi=10.1002%2fnme.5982&partnerID=40&md5=6aabcbdc9a0da25e36575a0ebfac034f
. POD–Galerkin Model Order Reduction for Parametrized Time Dependent Linear Quadratic Optimal Control Problems in Saddle Point Formulation. Journal of Scientific Computing. 2020 ;83.
. POD–Galerkin Model Order Reduction for Parametrized Time Dependent Linear Quadratic Optimal Control Problems in Saddle Point Formulation. Journal of Scientific Computing. 2020 ;83.
. POD–Galerkin monolithic reduced order models for parametrized fluid-structure interaction problems. International Journal Numerical Methods for Fluids. 2016 .
. POD–Galerkin reduced order methods for combined Navier–Stokes transport equations based on a hybrid FV-FE solver. Computers and Mathematics with Applications [Internet]. 2020 ;79:256-273. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068068567&doi=10.1016%2fj.camwa.2019.06.026&partnerID=40&md5=a8dcce1b53b8ee872d174bbc4c20caa3
. Projection-based reduced order models for a cut finite element method in parametrized domains. Computers and Mathematics with Applications [Internet]. 2020 ;79:833-851. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070900852&doi=10.1016%2fj.camwa.2019.08.003&partnerID=40&md5=2d222ab9c7832955d155655d3c93e1b1
. A Proper Orthogonal Decomposition Approach for Parameters Reduction of Single Shot Detector Networks. In: 2022 IEEE International Conference on Image Processing (ICIP). 2022 IEEE International Conference on Image Processing (ICIP). ; 2022.
. PyDMD: Python Dynamic Mode Decomposition. The Journal of Open Source Software [Internet]. 2018 ;3:530. Available from: https://joss.theoj.org/papers/734e4326edd5062c6e8ee98d03df9e1d
. PyGeM: Python Geometrical Morphing. Software Impacts. 2021 ;7:100047.
. A Reduced Basis Approach for Modeling the Movement of Nuclear Reactor Control Rods. NERS-14-1062; ASME J of Nuclear Rad Sci, 2, 2 (2016) 021019 [Internet]. 2016 ;2(2):8. Available from: http://urania.sissa.it/xmlui/handle/1963/35192
. A reduced basis approach for PDEs on parametrized geometries based on the shifted boundary finite element method and application to a Stokes flow. Computer Methods in Applied Mechanics and Engineering [Internet]. 2019 ;347:568-587. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060107322&doi=10.1016%2fj.cma.2018.12.040&partnerID=40&md5=1a3234f0cb000c91494d946428f8ebef
. Reduced basis approaches for parametrized bifurcation problems held by non-linear Von Kármán equations. [Internet]. 2019 ;81:112–135. Available from: https://arxiv.org/abs/1804.02014
. Reduced Basis Approaches for Parametrized Bifurcation Problems held by Non-linear Von Kármán Equations. Journal of Scientific Computing [Internet]. 2019 ;81:112-135. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068973907&doi=10.1007%2fs10915-019-01003-3&partnerID=40&md5=a09af83ce45183d6965cdb79d87a919b
. Reduced basis approaches in time-dependent noncoercive settings for modelling the movement of nuclear reactor control rods. Communications in Computational Physics [Internet]. 2016 ;(in press). Available from: http://urania.sissa.it/xmlui/handle/1963/34963
. Reduced Basis Approximation and A Posteriori Error Estimation: Applications to Elasticity Problems in Several Parametric Settings. In: Numerical Methods for PDEs. Vol. 15. Numerical Methods for PDEs. ; 2018. Available from: https://link.springer.com/chapter/10.1007/978-3-319-94676-4_8
. Reduced Basis Approximation and A Posteriori Error Estimation: Applications to Elasticity Problems in Several Parametric Settings. SEMA SIMAI Springer Series [Internet]. 2018 ;15:203-247. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055036627&doi=10.1007%2f978-3-319-94676-4_8&partnerID=40&md5=e9c07038e7bcc6668ec702c0653410dc