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Gabor Szederkenyi
Gábor Szederkényi received the M.Eng degree in computer engineering (University of Veszprém, 1998), his PhD in information sciences (University of Veszprém, 2002), and the DSc title in engineering ...vizualizați mai multeGábor Szederkényi received the M.Eng degree in computer engineering (University of Veszprém, 1998), his PhD in information sciences (University of Veszprém, 2002), and the DSc title in engineering sciences (Hungarian Academy of Sciences, 2013). Currently, he is a full professor at PPKE and the head of the Analysis and Control of Dynamical Systems research group. His main research interest is the computational analysis and control of nonlinear systems with special emphasis on reaction networks and kinetic models. He is the co-author of one book, several book chapters, more than 40 journal papers, and more than 60 conference papers on the theory and applicaton of the analysis and control of nonlinear systems. His education record includes BSc and MSc level courses on linear systems theory, nonlinear control and its application in robotics and in biological systems.
The history of the scientific cooperation of the proposed three authors dates back to 2003. Since then, they have published more than 25 joint scientific papers in international journals and conference proceedings mostly related to the topic of the proposed book. The scientific background of the three authors are really complementary: Prof. Katalin Hangos is an internationally known expert in the modelling and control of thermodynamical and (bio)chemical systems, Dr. Attila Magyar has significant experience in the analysis, application and control of quasi-polynomial systems, while Prof. Gábor Szederkényi has results on the optimization-based structural analysis and synthesis of kinetic systems. Moreover, all three authors have had continuous education and supervising experience both on the MSc and PhD levels at different universities.vizualizați mai puține
Cărți de Gabor Szederkenyi
Analysis and Control of Polynomial Dynamic Models with Biological Applications