Gianluigi Rozza

Orcid: 0000-0002-0810-8812

Affiliations:
  • International School for Advanced Studies (SISSA), Mathematics Area, Trieste, Italy


According to our database1, Gianluigi Rozza authored at least 209 papers between 2005 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
Linear and nonlinear filtering for a two-layer quasi-geostrophic ocean model.
Appl. Math. Comput., 2025

2024
Large-scale graph-machine-learning surrogate models for 3D-flowfield prediction in external aerodynamics.
Adv. Model. Simul. Eng. Sci., December, 2024

Mathematical modelling and computational reduction of molten glass fluid flow in a furnace melting basin.
Comput. Appl. Math., October, 2024

A Local Approach to Parameter Space Reduction for Regression and Classification Tasks.
J. Sci. Comput., June, 2024

Preface.
Comput. Math. Appl., February, 2024

Geometrically parametrised reduced order models for studying the hysteresis of the Coanda effect in finite element-based incompressible fluid dynamics.
J. Comput. Phys., 2024

Projection-based Reduced Order Modelling for Unsteady Parametrized Optimal Control Problems in 3D Cardiovascular Flows.
CoRR, 2024

Mesh-Informed Reduced Order Models for Aneurysm Rupture Risk Prediction.
CoRR, 2024

Data-driven reduced order modeling of a two-layer quasi-geostrophic ocean model.
CoRR, 2024

Data-driven Discovery of Delay Differential Equations with Discrete Delays.
CoRR, 2024

Non-intrusive model reduction of advection-dominated hyperbolic problems using neural network shift augmented manifold transformations.
CoRR, 2024

On the accuracy and efficiency of reduced order models: towards real-world applications.
CoRR, 2024

A time-adaptive algorithm for pressure dominated flows: a heuristic estimator.
CoRR, 2024

A hybrid reduced-order model for segregated fluid-structure interaction solvers in an ALE approach at high Reynolds number.
CoRR, 2024

Parametric Intrusive Reduced Order Models enhanced with Machine Learning Correction Terms.
CoRR, 2024

A brief review of Reduced Order Models using intrusive and non-intrusive techniques.
CoRR, 2024

Stabilized POD Reduced Order Models for convection-dominated incompressible flows.
CoRR, 2024

Computational study of numerical flux schemes for mesoscale atmospheric flows in a Finite Volume framework.
CoRR, 2024

A LSTM-enhanced surrogate model to simulate the dynamics of particle-laden fluid systems.
CoRR, 2024

Enhancing non-intrusive Reduced Order Models with space-dependent aggregation methods.
CoRR, 2024

Optimized Bayesian Framework for Inverse Heat Transfer Problems Using Reduced Order Methods.
CoRR, 2024

A stochastic perturbation approach to nonlinear bifurcating problems.
CoRR, 2024

A Predictive Surrogate Model for Heat Transfer of an Impinging Jet on a Concave Surface.
CoRR, 2024

Optimisation-Based Coupling of Finite Element Model and Reduced Order Model for Computational Fluid Dynamics.
CoRR, 2024

PyDMD: A Python package for robust dynamic mode decomposition.
CoRR, 2024

An optimisation-based domain-decomposition reduced order model for parameter-dependent non-stationary fluid dynamics problems.
Comput. Math. Appl., 2024

2023
An optimisation-based domain-decomposition reduced order model for the incompressible Navier-Stokes equations.
Comput. Math. Appl., December, 2023

A DeepONet multi-fidelity approach for residual learning in reduced order modeling.
Adv. Model. Simul. Eng. Sci., December, 2023

EZyRB: Easy Reduced Basis method.
Dataset, December, 2023

A two-stage deep learning architecture for model reduction of parametric time-dependent problems.
Comput. Math. Appl., November, 2023

EZyRB: Easy Reduced Basis method.
Dataset, November, 2023

A non-intrusive data-driven reduced order model for parametrized CFD-DEM numerical simulations.
J. Comput. Phys., October, 2023

A dimensionality reduction approach for convolutional neural networks.
Appl. Intell., October, 2023

EZyRB: Easy Reduced Basis method.
Dataset, October, 2023

A Dynamic Mode Decomposition Extension for the Forecasting of Parametric Dynamical Systems.
SIAM J. Appl. Dyn. Syst., September, 2023

EZyRB: Easy Reduced Basis method.
Dataset, September, 2023

EZyRB: Easy Reduced Basis method.
Dataset, August, 2023

Hybrid data-driven closure strategies for reduced order modeling.
Appl. Math. Comput., July, 2023

EZyRB: Easy Reduced Basis method.
Dataset, July, 2023

PINA: Physics-Informed Neural networks for Advanced modeling.
Dataset, July, 2023

EZyRB: Easy Reduced Basis method.
Dataset, June, 2023

EZyRB: Easy Reduced Basis method.
Dataset, May, 2023

Towards a Machine Learning Pipeline in Reduced Order Modelling for Inverse Problems: Neural Networks for Boundary Parametrization, Dimensionality Reduction and Solution Manifold Approximation.
J. Sci. Comput., April, 2023

A data-driven surrogate modeling approach for time-dependent incompressible Navier-Stokes equations with dynamic mode decomposition and manifold interpolation.
Adv. Comput. Math., April, 2023

EZyRB: Easy Reduced Basis method.
Dataset, April, 2023

Pressure data-driven variational multiscale reduced order models.
J. Comput. Phys., March, 2023

EZyRB: Easy Reduced Basis method.
Dataset, March, 2023

Non-linear Manifold Reduced-Order Models with Convolutional Autoencoders and Reduced Over-Collocation Method.
J. Sci. Comput., February, 2023

Data-Driven Reduced Order Modelling for Patient-Specific Hemodynamics of Coronary Artery Bypass Grafts with Physical and Geometrical Parameters.
J. Sci. Comput., 2023

Projection Based Semi-Implicit Partitioned Reduced Basis Method for Fluid-Structure Interaction Problems.
J. Sci. Comput., 2023

Physics-Informed Neural networks for Advanced modeling.
J. Open Source Softw., 2023

A hybrid projection/data-driven reduced order model for the Navier-Stokes equations with nonlinear filtering stabilization.
J. Comput. Phys., 2023

A novel Large Eddy Simulation model for the Quasi-Geostrophic equations in a Finite Volume setting.
J. Comput. Appl. Math., 2023

Physics Informed Neural Network Framework for Unsteady Discretized Reduced Order System.
CoRR, 2023

Modal Analysis of the Wake Shed Behind a Horizontal Axis Wind Turbine with Flexible Blades.
CoRR, 2023

Deep Reinforcement Learning for the Heat Transfer Control of Pulsating Impinging Jets.
CoRR, 2023

Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel.
CoRR, 2023

Generative Models for the Deformation of Industrial Shapes with Linear Geometric Constraints: model order and parameter space reductions.
CoRR, 2023

Explicable hyper-reduced order models on nonlinearly approximated solution manifolds of compressible and incompressible Navier-Stokes equations.
CoRR, 2023

Friedrichs' systems discretized with the Discontinuous Galerkin method: domain decomposable model order reduction and Graph Neural Networks approximating vanishing viscosity solutions.
CoRR, 2023

Reduced order models for the buckling of hyperelastic beams.
CoRR, 2023

Generative Adversarial Reduced Order Modelling.
CoRR, 2023

A reduced-order model for segregated fluid-structure interaction solvers based on an ALE approach.
CoRR, 2023

Filter stabilization for the mildly compressible Euler equations with application to atmosphere dynamics simulations.
CoRR, 2023

A shape optimization pipeline for marine propellers by means of reduced order modeling techniques.
CoRR, 2023

A physics-based reduced order model for urban air pollution prediction.
CoRR, 2023

Applicable Methodologies for the Mass Transfer Phenomenon in Tumble Dryers: A Review.
CoRR, 2023

Model Order Reduction for Deforming Domain Problems in a Time-Continuous Space-Time Setting.
CoRR, 2023

Weighted reduced order methods for uncertainty quantification in computational fluid dynamics.
CoRR, 2023

A Graph-based Framework for Complex System Simulating and Diagnosis with Automatic Reconfiguration.
CoRR, 2023

Reduced Basis, Embedded Methods and Parametrized Levelset Geometry.
CoRR, 2023

A two stages Deep Learning Architecture for Model Reduction of Parametric Time-Dependent Problems.
CoRR, 2023

Stabilized Weighted Reduced Order Methods for Parametrized Advection-Dominated Optimal Control Problems governed by Partial Differential Equations with Random Inputs.
CoRR, 2023

A Streamline upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations under Optimal Control.
CoRR, 2023

An extended physics informed neural network for preliminary analysis of parametric optimal control problems.
Comput. Math. Appl., 2023

2022
Reduced basis methods for time-dependent problems.
Acta Numer., May, 2022

Verifiability of the Data-Driven Variational Multiscale Reduced Order Model.
J. Sci. Comput., 2022

Scientific Machine Learning Through Physics-Informed Neural Networks: Where we are and What's Next.
J. Sci. Comput., 2022

POD-Galerkin model order reduction for parametrized nonlinear time-dependent optimal flow control: an application to shallow water equations.
J. Num. Math., 2022

Neural-network learning of SPOD latent dynamics.
J. Comput. Phys., 2022

Assessment of URANS and LES Methods in Predicting Wake Shed Behind a Vertical Axis Wind Turbine.
CoRR, 2022

Non-intrusive reduced order models for the accurate prediction of bifurcating phenomena in compressible fluid dynamics.
CoRR, 2022

Deep learning-based reduced-order methods for fast transient dynamics.
CoRR, 2022

A linear filter regularization for POD-based reduced order models of the quasi-geostrophic equations.
CoRR, 2022

A Continuous Convolutional Trainable Filter for Modelling Unstructured Data.
CoRR, 2022

A unified steady and unsteady formulation for hydrodynamic potential flow simulations with fully nonlinear free surface boundary conditions.
CoRR, 2022

Novel Methodologies for Solving the Inverse Unsteady Heat Transfer Problem of Estimating the Boundary Heat Flux in Continuous Casting Molds.
CoRR, 2022

A data-driven Reduced Order Method for parametric optimal blood flow control: application to coronary bypass graft.
CoRR, 2022

A multi-fidelity approach coupling parameter space reduction and non-intrusive POD with application to structural optimization of passenger ship hulls.
CoRR, 2022

A segregated reduced order model of a pressure-based solver for turbulent compressible flows.
CoRR, 2022

An introduction to POD-Greedy-Galerkin reduced basis method.
CoRR, 2022

Non-linear manifold ROM with Convolutional Autoencoders and Reduced Over-Collocation method.
CoRR, 2022

Towards a Numerical Proof of Turbulence Closure.
CoRR, 2022

Data-Driven Enhanced Model Reduction for Bifurcating Models in Computational Fluid Dynamics.
CoRR, 2022

Embedded domain Reduced Basis Models for the shallow water hyperbolic equations with the Shifted Boundary Method.
CoRR, 2022

Reduced order modeling for spectral element methods: current developments in Nektar++ and further perspectives.
CoRR, 2022

Projection based semi-implicit partitioned Reduced Basis Method for non parametrized and parametrized Fluid-Structure Interaction problems.
CoRR, 2022

Model Reduction Using Sparse Polynomial Interpolation for the Incompressible Navier-Stokes Equations.
CoRR, 2022

Fast and accurate numerical simulations for the study of coronary artery bypass grafts by artificial neural network.
CoRR, 2022

A POD-Galerkin reduced order model for the Navier-Stokes equations in stream function-vorticity formulation.
CoRR, 2022

A Reduced Order Cut Finite Element method for geometrically parametrized steady and unsteady Navier-Stokes problems.
Comput. Math. Appl., 2022

A Proper Orthogonal Decomposition Approach for Parameters Reduction of Single Shot Detector Networks.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021
Benchmarks inverse heat transfer problem: Boundary heat flux estimation in continuous casting mold.
Dataset, August, 2021

PyGeM: Python Geometrical Morphing.
Softw. Impacts, 2021

ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis.
Softw. Impacts, 2021

A Supervised Learning Approach Involving Active Subspaces for an Efficient Genetic Algorithm in High-Dimensional Optimization Problems.
SIAM J. Sci. Comput., 2021

Hierarchical Model Reduction Techniques for Flow Modeling in a Parametrized Setting.
Multiscale Model. Simul., 2021

A Reduced Order Model for a Stable Embedded Boundary Parametrized Cahn-Hilliard Phase-Field System Based on Cut Finite Elements.
J. Sci. Comput., 2021

A POD-Galerkin reduced order model for a LES filtering approach.
J. Comput. Phys., 2021

A data-driven partitioned approach for the resolution of time-dependent optimal control problems with dynamic mode decomposition.
CoRR, 2021

Finite element based model order reduction for parametrized one-way coupled steady state linear thermomechanical problems.
CoRR, 2021

Multi-fidelity data fusion through parameter space reduction with applications to automotive engineering.
CoRR, 2021

An efficient FV-based Virtual Boundary Method for the simulation of fluid-solid interaction.
CoRR, 2021

Neural-network learning of SPOD latent dynamics.
CoRR, 2021

Model order reduction for bifurcating phenomena in Fluid-Structure Interaction problems.
CoRR, 2021

Consistency of the Full and Reduced Order Models for Evolve-Filter-Relax Regularization of Convection-Dominated, Marginally-Resolved Flows.
CoRR, 2021

An artificial neural network approach to bifurcating phenomena in computational fluid dynamics.
CoRR, 2021

Thermomechanical modelling for industrial applications.
CoRR, 2021

The Neural Network shifted-Proper Orthogonal Decomposition: a Machine Learning Approach for Non-linear Reduction of Hyperbolic Equations.
CoRR, 2021

A Hybrid Reduced Order Model for nonlinear LES filtering.
CoRR, 2021

Hybrid neural network reduced order modelling for turbulent flows with geometric parameters.
CoRR, 2021

Pressure stabilization strategies for a LES filtering Reduced Order Model.
CoRR, 2021

An optimal control approach to determine resistance-type boundary conditions from in-vivo data for cardiovascular simulations.
CoRR, 2021

A monolithic and a partitioned Reduced Basis Method for Fluid-Structure Interaction problems.
CoRR, 2021

A Reduced basis stabilization for the unsteady Stokes and Navier-Stokes equations.
CoRR, 2021

A Certified Reduced Basis Method for Linear Parametrized Parabolic Optimal Control Problems in Space-Time Formulation.
CoRR, 2021

Fluid-structure interaction simulations with a LES filtering approach in solids4Foam.
CoRR, 2021

A numerical approach for heat flux estimation in thin slabs continuous casting molds using data assimilation.
CoRR, 2021

Hull shape design optimization with parameter space and model reductions, and self-learning mesh morphing.
CoRR, 2021

A weighted POD-reduction approach for parametrized PDE-constrained optimal control problems with random inputs and applications to environmental sciences.
Comput. Math. Appl., 2021

Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method.
Adv. Comput. Math., 2021

2020
A Reduced Order Modeling Technique to Study Bifurcating Phenomena: Application to the Gross-Pitaevskii Equation.
SIAM J. Sci. Comput., 2020

POD-Galerkin Model Order Reduction for Parametrized Time Dependent Linear Quadratic Optimal Control Problems in Saddle Point Formulation.
J. Sci. Comput., 2020

Data-driven POD-Galerkin reduced order model for turbulent flows.
J. Comput. Phys., 2020

Gaussian process approach within a data-driven POD framework for fluid dynamics engineering problems.
CoRR, 2020

Reduced order methods for parametric flow control problems and applications.
CoRR, 2020

Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier-Stokes equations with model order reduction.
CoRR, 2020

Multi-fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces.
CoRR, 2020

A non-intrusive data-driven ROM framework for hemodynamics problems.
CoRR, 2020

A comparison of reduced-order modeling approaches for PDEs with bifurcating solutions.
CoRR, 2020

A Reduced Order Cut Finite Element method for geometrically parameterized steady and unsteady Navier-Stokes problems.
CoRR, 2020

Kernel-based Active Subspaces with application to CFD parametric problems using Discontinuous Galerkin method.
CoRR, 2020

Non-intrusive PODI-ROM for patient-specific aortic blood flow in presence of a LVAD device.
CoRR, 2020

On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis.
CoRR, 2020

MicroROM: An Efficient and Accurate Reduced Order Method to Solve Many-Query Problems in Micro-Motility.
CoRR, 2020

An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques.
CoRR, 2020

Projection-based reduced order models for a cut finite element method in parametrized domains.
Comput. Math. Appl., 2020

POD-Galerkin reduced order methods for combined Navier-Stokes transport equations based on a hybrid FV-FE solver.
Comput. Math. Appl., 2020

Certified Reduced Basis VMS-Smagorinsky model for natural convection flow in a cavity with variable height.
Comput. Math. Appl., 2020

Stabilized reduced basis methods for parametrized steady Stokes and Navier-Stokes equations.
Comput. Math. Appl., 2020

Enhancing CFD predictions in shape design problems by model and parameter space reduction.
Adv. Model. Simul. Eng. Sci., 2020

2019
BladeX: Python Blade Morphing.
Dataset, February, 2019

A Weighted POD Method for Elliptic PDEs with Random Inputs.
J. Sci. Comput., 2019

Reduced Basis Approaches for Parametrized Bifurcation Problems held by Non-linear Von Kármán Equations.
J. Sci. Comput., 2019

Preface: Special Issue on Model Reduction.
J. Sci. Comput., 2019

BladeX: Python Blade Morphing.
J. Open Source Softw., 2019

Extension and comparison of techniques to enforce boundary conditions in Finite Volume POD-Galerkin reduced order models for fluid dynamic problems.
CoRR, 2019

Basic Ideas and Tools for Projection-Based Model Reduction of Parametric Partial Differential Equations.
CoRR, 2019

Overcoming slowly decaying Kolmogorov n-width by transport maps: application to model order reduction of fluid dynamics and fluid-structure interaction problems.
CoRR, 2019

Reduced order methods for parametric optimal flow control in coronary bypass grafts, towards patient-specific data assimilation.
CoRR, 2019

A non-intrusive approach for proper orthogonal decomposition modal coefficients reconstruction through active subspaces.
CoRR, 2019

A Reduced-Order Shifted Boundary Method for Parametrized incompressible Navier-Stokes equations.
CoRR, 2019

A Reduced Order technique to study bifurcating phenomena: application to the Gross-Pitaevskii equation.
CoRR, 2019

A Hybrid Reduced Order Method for Modelling Turbulent Heat Transfer Problems.
CoRR, 2019

Efficient Reduction in Shape Parameter Space Dimension for Ship Propeller Blade Design.
CoRR, 2019

A reduced order variational multiscale approach for turbulent flows.
Adv. Comput. Math., 2019

Reduced Order Methods for Parametrized Non-linear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences.
Proceedings of the Numerical Mathematics and Advanced Applications ENUMATH 2019 - European Conference, Egmond aan Zee, The Netherlands, September 30, 2019

Discontinuous Galerkin Model Order Reduction of Geometrically Parametrized Stokes Equation.
Proceedings of the Numerical Mathematics and Advanced Applications ENUMATH 2019 - European Conference, Egmond aan Zee, The Netherlands, September 30, 2019

2018
EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

EZyRB: Easy Reduced Basis method.
Dataset, April, 2018

PyDMD: Python Dynamic Mode Decomposition.
Dataset, February, 2018

Model Reduction for Parametrized Optimal Control Problems in Environmental Marine Sciences and Engineering.
SIAM J. Sci. Comput., 2018

Stabilized Weighted Reduced Basis Methods for Parametrized Advection Dominated Problems with Random Inputs.
SIAM/ASA J. Uncertain. Quantification, 2018

Certified Reduced Basis Approximation for the Coupling of Viscous and Inviscid Parametrized Flow Models.
J. Sci. Comput., 2018

EZyRB: Easy Reduced Basis method.
J. Open Source Softw., 2018

PyDMD: Python Dynamic Mode Decomposition.
J. Open Source Softw., 2018

Dimension reduction in heterogeneous parametric spaces with application to naval engineering shape design problems.
Adv. Model. Simul. Eng. Sci., 2018

2017
On a Certified Smagorinsky Reduced Basis Turbulence Model.
SIAM J. Numer. Anal., 2017

Reduced Basis Methods for Uncertainty Quantification.
SIAM/ASA J. Uncertain. Quantification, 2017

On the Application of Reduced Basis Methods to Bifurcation Problems in Incompressible Fluid Dynamics.
J. Sci. Comput., 2017

Computational reduction strategies for the detection of steady bifurcations in incompressible fluid-dynamics: Applications to Coanda effect in cardiology.
J. Comput. Phys., 2017

2016
Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations.
Numerische Mathematik, 2016

Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization.
J. Comput. Phys., 2016

Reduced basis method and domain decomposition for elliptic problems in networks and complex parametrized geometries.
Comput. Math. Appl., 2016

Isogeometric analysis-based reduced order modelling for incompressible linear viscous flows in parametrized shapes.
Adv. Model. Simul. Eng. Sci., 2016

2015
Reduced basis approximation of parametrized optimal flow control problems for the Stokes equations.
Comput. Math. Appl., 2015

Reduced basis approximation and a-posteriori error estimation for the coupled Stokes-Darcy system.
Adv. Comput. Math., 2015

Model order reduction of parameterized systems (MoRePaS) - Preface to the special issue of advances in computational mathematics.
Adv. Comput. Math., 2015

2014
Comparison Between Reduced Basis and Stochastic Collocation Methods for Elliptic Problems.
J. Sci. Comput., 2014

Shape Optimization by Free-Form Deformation: Existence Results and Numerical Solution for Stokes Flows.
J. Sci. Comput., 2014

2013
Reduced Basis Method for Parametrized Elliptic Optimal Control Problems.
SIAM J. Sci. Comput., 2013

A Weighted Reduced Basis Method for Elliptic Partial Differential Equations with Random Input Data.
SIAM J. Numer. Anal., 2013

Stochastic Optimal Robin Boundary Control Problems of Advection-Dominated Elliptic Equations.
SIAM J. Numer. Anal., 2013

Reduced basis approximation and a posteriori error estimation for Stokes flows in parametrized geometries: roles of the inf-sup stability constants.
Numerische Mathematik, 2013

Reduced Basis Approximation of Parametrized Advection-Diffusion PDEs with High Péclet Number.
Proceedings of the Numerical Mathematics and Advanced Applications - ENUMATH 2013, 2013

2012
A Reduced Basis Model with Parametric Coupling for Fluid-Structure Interaction Problems.
SIAM J. Sci. Comput., 2012

A Reduced-Order Strategy for Solving Inverse Bayesian Shape Identification Problems in Physiological Flows.
Proceedings of the Modeling, Simulation and Optimization of Complex Processes, 2012

2011
Reduction Strategies for Shape Dependent Inverse Problems in Haemodynamics.
Proceedings of the System Modeling and Optimization, 2011

2009
Reduced basis method for multi-parameter-dependent steady Navier-Stokes equations: Applications to natural convection in a cavity.
J. Comput. Phys., 2009

2006
Shape Design in Aorto-Coronaric Bypass Anastomoses Using Perturbation Theory.
SIAM J. Numer. Anal., 2006

A Mathematical Approach in the Design of Arterial Bypass Using Unsteady Stokes Equations.
J. Sci. Comput., 2006

2005
Numerical Approximation of a Control Problem for Advection-Diffusion Processes.
Proceedings of the System Modeling and Optimization, 2005


  Loading...