
Laura Meneghetti
20212022 
Nirav Shah
20212022Related publication(s):

Marco Tezzele
20202021Related publication(s):
 Kernelbased active subspaces with application to computational fluid dynamics parametric problems using discontinuous Galerkin method (2022)
 A supervised learning approach involving active subspaces for an efficient genetic algorithm in highdimensional optimization problems (2021)
 On the comparison of LES datadriven reduced order approaches for hydroacoustic analysis (2021)
 Hull Shape Design Optimization with Parameter Space and Model Reductions, and SelfLearning Mesh Morphing (2021)
 ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis (2021)
 Multifidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces (2021)
 A local approach to parameter space reduction for regression and classification tasks (2021)
 Multifidelity data fusion through parameter space reduction with applications to automotive engineering (2021)
 Enhancing CFD predictions in shape design problems by model and parameter space reduction (2020)
 Reduced order isogeometric analysis approach for pdes in parametrized domains (2020)
 Advances in reduced order methods for parametric industrial problems in computational fluid dynamics (2020)
 Basic ideas and tools for projectionbased model reduction of parametric partial differential equations (2020)
 Kernelbased Active Subspaces with application to CFD parametric problems using Discontinuous Galerkin method (2020)
 A nonintrusive approach for the reconstruction of POD modal coefficients through active subspaces (2019)

Federico Pichi
20192020Related publication(s):
 Model order reduction for bifurcating phenomena in fluidstructure interaction problems (2022)
 Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier–Stokes equations with model order reduction (2022)
 Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method (2020)
 A Reduced Order technique to study bifurcating phenomena: application to the GrossPitaevskii equation (2020)
 Reduced basis approaches for parametrized bifurcation problems held by nonlinear Von Kármán equations (2019)
 Reduced Basis Approximation and A Posteriori Error Estimation: Applications to Elasticity Problems in Several Parametric Settings (2018)

Monica Nonino
20192020Related publication(s):
 An optimisationbased domaindecomposition reduced order model for the incompressible NavierStokes equations (2022)
 A Monolithic and a Partitioned, Reduced Basis Method for Fluid–Structure Interaction Problems (2021)
 A Reduced Order Cut Finite Element method for geometrically parametrized steady and unsteady Navier–Stokes problems (2021)

Saddam Hijazi
20192020Related publication(s):
 The Effort of Increasing Reynolds Number in ProjectionBased Reduced Order Methods: from Laminar to Turbulent Flows (2020)
 Nonintrusive Polynomial Chaos Method Applied to FullOrder and Reduced Problems in Computational Fluid Dynamics: A Comparison and Perspectives (2020)
 Datadriven PODGalerkin reduced order model for turbulent flows (2020)
 PODGalerkin reduced order methods for CFD using Finite Volume Discretisation: vortex shedding around a circular cylinder (2017)

Zakia Zainib
20182019Related publication(s):
 Reduced Order Methods for Parametrized Nonlinear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences (2021)
 Reduced Order Methods for Parametrized Nonlinear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences (2021)
 Reduced order methods for parametric optimal flow control in coronary bypass grafts, toward patientspecific data assimilation (2020)

Shafqat Ali
20172018Stabilized reduced basis methods for the approximation of parametrized viscous flowsRelated publication(s):

Umberto Emil Morelli