MARCO GILLI

Marco Gilli is an expert in nonlinear circuits and systems and cellular nonlinear network dynamics. He received the PhD degree in Electronics Engineering from the Technical University of Torino (Politecnico di Torino), Italy and he is currently Vice Dean (responsible for 2nd Level Teaching Services) and Full Professor of Electrical Engineering at the First Faculty of Engineering of the same University. He is author or coauthor of more than 110 technical papers. In 1994 he received the best paper award from the International Journal of Circuit Theory and Applications. In 1998 Marco Gilli won the Ravani prize, awarded by the Academy of Science of Torino (Italy), for contributions to Physics and in particular to Electrical Engineering (in occasion of the centenary of the death of the Italian scientist Galileo Ferraris). From 1999 to 2003 Marco

Gilli was Associate Editor of the IEEE, Transactions on Circuits and Systems: part I, for the areas of "Nonlinear circuits and systems" (1999-2001) and "Chaos and bifurcations" (2002-2003). He was "Distinguished Lecturer" of the IEEE CAS Society (2002-2003). He has served and he is serving as a member of the scientific committee of several international conferences and he has organized several special sessions at major CAS related conferences. Marco Gilli is the Secretary of the CAS Committee on “Cellular neural networks and array computing” and he is a member of CAS Committee on “Nonlinear circuits and systems.” He is currently the Chair of the CAS Chapter of the IEEE North Italy Section. Since 2005 Marco Gilli has been a Fellow of the IEEE. He is currently the President of the “Italian Society of Chaos and Complexity

 Marco Gilli has given substantial contributions to stability properties and global dynamic behavior of cellular nonlinear networks. In particular: 1) he has proved some significant theorems on complete stability of non-symmetric CNNs, holding also in presence of delay and of non-monotonic output functions; 2) he has developed a rigorous technique for predicting the steady-state dynamic behavior of binary CNNs, which allows one to establish rigorous design algorithms; 3) he has developed some spectral techniques for characterizing the global dynamic behavior of complex large scale CNNs, i.e. for accurately estimating the whole sets of attractors and the most significant bifurcation phenomena.

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