Galvanin, Federico - University College London - Department of Chemical Engineering

个人简介

Master’s degree, University of Padova, Italy, 2006 PhD in Industrial Engineering, University of Padova, Italy, 2010

研究领域

Design of Experiments (DoE) and statistical planning Model-based Design of Experiments (MBDoE) for model identification Kinetic modelling, modelling of reaction systems Pharmacokinetics/pharmacodynamics modelling Modelling of physiological systems Parameter Estimation

近期论文

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Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. (2016). A joint model-based experimental design approach for the identification of kinetic models in continuous flow laboratory reactors. COMPUTERS & CHEMICAL ENGINEERING, 95, 202-215. doi:10.1016/j.compchemeng.2016.05.009 De-Luca, R., Galvanin, F., & Bezzo, F. (2016). A methodology for direct exploitation of available information in the online model-based redesign of experiments. Computers & Chemical Engineering, 91, 195-205. doi:10.1016/j.compchemeng.2016.03.016 Quaglio, M., Bezzo, F., Gavriilidis, A., Cao, E., & Galvanin, F. (2016). A MINLP approach to model-based data mining for the quick development of nonlinear dynamic models. AIChE Annual Meeting, Conference Proceedings. Galvanin, F., Psyrraki, C., Morris, T., & Gavriilidis, A. (2016). A ranking of experiments approach for the identification of kinetic models of ethylene methoxycarbonylation in capillary microreactors. XXII International conference on Chemical Reactors (CHEMREACTOR-22), Conference Proceedings. Al-Rifai, N., Galvanin, F., Morad, M., Cao, E., Cattaneo, S., Sankar, M., . . . Gavriilidis, A. (2016). Hydrodynamic effects on three phase micro-packed bed reactor performance - Gold-palladium catalysed benzyl alcohol oxidation. Chemical Engineering Science, 149, 129-142. doi:10.1016/j.ces.2016.03.018 Galvanin, F., Al-Rifai, N., Cao, E., Sankar, M., Hutchings, G., Gavriilidis, A., & Dua, V. (2016). Merging information from batch and continuous flow experiments for the identification of kinetic models of benzyl alcohol oxidation over Au-Pd catalyst. Galvanin, F., Marchesini, R., Barolo, M., Bezzo, F., & Fidaleo, M. (2016). Optimal design of experiments for parameter identification in electrodialysis models. CHEMICAL ENGINEERING RESEARCH & DESIGN, 105, 107-119. doi:10.1016/j.cherd.2015.10.048 Pradella, D., Bezzo, F., & Galvanin, F. (2016). Optimal Design of Feasible Clinical Tests for the Identification of Physiological Models of Type 1 Diabetes Mellitus. AIChE Annual Meeting, Conference Proceedings. Huang, C., Piccione, P. M., Cattani, F., & Galvanin, F. (2016). Travelling traders’ exchange problem: stochastic simulation and sensitivity analysis. AIChE Annual Meeting, Conference Proceedings. De Luca, R., Galvanin, F., & Bezzo, F. (2015). A framework for a direct exploitation of available information in the online model-based redesign of experiments. Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. (2015). A model-based experimental design study for the development of kinetic models of methanol oxidation on silver catalyst. Proceedings of CAPE Forum 2015, 87-93. Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. (2015). Model-based design of experiments for the identification of kinetic models in microreactor platforms. Amsterdam (The Netherlands): Elsevier. Galvanin, F., Cao, E., Al-Rifai, N., Dua, V., & Gavriilidis, A. (2015). Optimal design of experiments for the identification of kinetic models of methanol oxidation over silver catalyst. Chemistry Today, 33 (3), 51-56. Galvanin, F., Barolo, M., Padrini, R., Casonato, A., & Bezzo, F. (2014). A model-based approach to the automatic diagnosis of von Willebrand disease. AIChE Journal, 60 (5), 1718-1727. doi:10.1002/aic.14373 Bernardi, A., Perin, G., Sforza, E., Galvanin, F., Morosinotto, T., & Bezzo, F. (2014). An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth. Industrial & Engineering Chemistry Research. doi:10.1021/ie500523z Galvanin, F., De Luca, R., Ferrentino, G., Barolo, M., Spilimbergo, S., & Bezzo, F. (2014). Bacterial inactivation on solid food matrices through supercritical CO2: A correlative study. Journal of Food Engineering, 120, 146-157. doi:10.1016/j.jfoodeng.2013.07.027 Galvanin, F., Monte, A., Casonato, A., Padrini, R., Barolo, M., & Bezzo, F. (2014). Towards Model-Based Diagnosis of von Willebrand Disease. In P. S. V. Jiří Jaromír Klemeš, P. Y. Liew (Eds.), 24th European Symposium on Computer Aided Process Engineering (p. 583 - 588). Elsevier. doi:10.1016/B978-0-444-63456-6.50098-3 Galvanin, F., Ballan, C. C., Barolo, M., & Bezzo, F. (2013). A general model-based design of experiments approach to achieve practical identifiability of pharmacokinetic and pharmacodynamic models. Journal of Pharmacokinetics and Pharmacodynamics, 40 (4), 451-467. doi:10.1007/s10928-013-9321-5 Galvanin, F., Barolo, M., Bonadonna, R. C., & Bezzo, F. (2013). Identification of complex models of type 2 diabetes from IVGTT data by model-based design of experiments. Computer Aided Chemical Engineering, 32, 133-138. Bernardi, A., Perin, G., Galvanin, F., Morosinotto, T., & Bezzo, F. (2013). Modeling the effect of light intensity in microalgae growth. Galvanin, F., Barolo, M., & Bezzo, F. (2013). On the use of continuous glucose monitoring systems to design optimal clinical tests for the identification of type 1 diabetes models. Computer Methods and Programs in Biomedicine, 109 (2), 157-170. doi:10.1016/j.cmpb.2012.02.010 Galvanin, F., Barolo, M., Pannocchia, G., & Bezzo, F. (2012). Online model-based redesign of experiments with erratic models: A disturbance estimation approach. Computers & Chemical Engineering, 42, 138-151. doi:10.1016/j.compchemeng.2011.11.014 Ballan, C. C., Galvanin, F., Barolo, M., & Bezzo, F. (2012). Parallel design of pharmacodynamic experiments for the identification of antimicrobial-resistant bacterial population models. Computer Aided Chemical Engineering, 31, 1125-1129. Galvanin, F., Barolo, M., Pannocchia, G., & Bezzo, F. (2011). A disturbance estimation approach for online model-based redesign of experiments in the presence of systematic errors. Computer Aided Chemical Engineering, 29, 467-471. Galvanin, F., Barolo, M., Macchietto, S., & Bezzo, F. (2011). Identification of Physiological Models of Type 1 Diabetes Mellitus by Model-Based Design of Experiments. null (pp. 545-581).