Federico Galvanin

18 papers Journal 18
YearRankTypeTitle / Venue / Authors
2025 J jnl
DoE-SINDy: an automated framework for model generation and selection in kinetic studies.
Comput. Chem. Eng.
Wenyao Lyu, Federico Galvanin
2025 J jnl
Model-based design of experiments for efficient and accurate isotherm model identification in High Performance Liquid Chromatography.
Comput. Chem. Eng.
Konstantinos Katsoulas, Federico Galvanin, Luca Mazzei, Maximilian O. Besenhard, Eva Sørensen
2024 J jnl
An optimal experimental design framework for fast kinetic model identification based on artificial neural networks.
Comput. Chem. Eng.
Enrico Sangoi, Marco Quaglio, Fabrizio Bezzo, Federico Galvanin
2024 J jnl
An optimization-free Fisher information driven approach for online design of experiments.
Comput. Chem. Eng.
Andrea Friso, Federico Galvanin
2023 J jnl
An exploratory model-based design of experiments approach to aid parameters identification and reduce model prediction uncertainty.
Comput. Chem. Eng.
Francesca Cenci, Arun Pankajakshan, Pierantonio Facco, Federico Galvanin
2023 J jnl
An optimal experimental design strategy for improving parameter estimation in stochastic models.
Comput. Chem. Eng.
Chunbing Huang, Federica Cattani, Federico Galvanin
2021 J jnl
Safe model-based design of experiments using Gaussian processes.
Comput. Chem. Eng.
Panagiotis Petsagkourakis, Federico Galvanin
2020 J jnl
A diagnostic procedure for improving the structure of approximated kinetic models.
Comput. Chem. Eng.
Marco Quaglio, Eric S. Fraga, Federico Galvanin
2020 J jnl
An artificial neural network approach to recognise kinetic models from experimental data.
Comput. Chem. Eng.
Marco Quaglio, Louise Roberts, Mohd Safarizal Bin Jaapar, Eric S. Fraga, Vivek Dua, Federico Galvanin
2020 J jnl
Chance Constrained Policy Optimization for Process Control and Optimization.
CoRR
Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Federico Galvanin, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
2020 J jnl
Safe model-based design of experiments using Gaussian processes.
CoRR
Panagiotis Petsagkourakis, Federico Galvanin
2019 J jnl
A framework for the optimal design of a minimum set of clinical trials to characterize von Willebrand disease.
Comput. Methods Programs Biomed.
B. Taverna, A. Casonato, Fabrizio Bezzo, Federico Galvanin
2019 J jnl
An online reparametrisation approach for robust parameter estimation in automated model identification platforms.
Comput. Chem. Eng.
Marco Quaglio, Conor Waldron, Arun Pankajakshan, Enhong Cao, Asterios Gavriilidis, Eric S. Fraga, Federico Galvanin
2016 J jnl
A joint model-based experimental design approach for the identification of kinetic models in continuous flow laboratory reactors.
Comput. Chem. Eng.
Federico Galvanin, Enhong Cao, Noor Al-Rifai, Asterios Gavriilidis, Vivek Dua
2016 J jnl
A methodology for direct exploitation of available information in the online model-based redesign of experiments.
Comput. Chem. Eng.
Riccardo De Luca, Federico Galvanin, Fabrizio Bezzo
2013 J jnl
On the use of continuous glucose monitoring systems to design optimal clinical tests for the identification of type 1 diabetes models.
Comput. Methods Programs Biomed.
Federico Galvanin, Massimiliano Barolo, Fabrizio Bezzo
2012 J jnl
Online model-based redesign of experiments with erratic models: A disturbance estimation approach.
Comput. Chem. Eng.
Federico Galvanin, Massimiliano Barolo, Gabriele Pannocchia, Fabrizio Bezzo
2011 J jnl
Optimal design of clinical tests for the identification of physiological models of type 1 diabetes in the presence of model mismatch.
Medical Biol. Eng. Comput.
Federico Galvanin, Massimiliano Barolo, Sandro Macchietto, Fabrizio Bezzo