Personal Information

Name/Last Name             Alessandra Fanni

E-mail   fanni@diee.unica.it

Alessandra Fanni received the Laurea degree in electrical engineering from the University of Cagliari, Cagliari, Italy, in 1981. She is currently a Full Professor of Circuit Theory with the Department of Electrical and Electronic Engineering, University of Cagliari. She coordinates several research projects, and she is the Scientific Coordinator responsible for some research contracts for young researchers, research fellows, research contractors, and Ph.D. students. Since 1990 is the holder of several teaching courses of her scientific sector and related sectors mainly in the Faculty of Engineering. She has had and has managerial responsibilities, coordination, and representation in academic bodies of the University of Cagliari (Member of the Academic Senate, Scientific Coordinator of the Industrial and Information Engineering, Coordinator of the PhD in Industrial Engineering, Director of the PhD school in Industrial Engineering, member of the Scientific Committee of the Liaison Office), and responsible of research laboratories and facilities (coordinator of the Laboratory of Industrial Engineering and Computer Science, located at Polaris Science and Technology Park in Sardinia, Activity Manager of the research on Optimization of Multiservice networks within the Information and Communication Engineering Laboratory, at Tiscali SpA).

Her research interests include the following main areas: circuit theory, system and signal theory, combinatorial optimization algorithms for energy and telecommunication networks, numerical methods for electromagnetic fields and electromagnetic compatibility, neural networks, and fusion engineering. She is the author of more than 350 international and national papers, over 140 of which are indexed by Scopus and ISI Web of Science, from 1990 to 2019. Her papers received more than 1000 citations, and her h-index is 17 (Scopus).

She contributed to the study of original optimization algorithms and architectures of neural networks for classification and prediction of time series and for the application of the same to diagnosis, identification problems, analysis of mono- and multidimensional data, communication networks, and fusion engineering.