Giorgio Picci


Giorgio Picci is an Italian electrical engineer and control theorist. He has made widely recognized contributions to the field of Systems and Control, and in particular, to the areas of Stochastic Realization and System Identification. He was also a pioneer in Computer Vision. He has published a monograph and over 150 papers in these areas.
He is currently a Professor Emeritus with the Department of Information Engineering, University of Padua, Italy. He is also the Italian director of the Confucius Institute at the University of Padua, where he actively promotes cultural and scientific exchanges between China and Italy, in collaborations with Guangzhou University in China.

Biography

Picci obtained the Doctor in Engineering degree from the University of Padua in 1967. From 1980 to 2012, he was the Chair Professor in System Identification at the Department of Information Engineering, University of Padua. During his career, he had a number of visiting positions with different universities on three continents, namely North America, Europe, and Asia.
Picci is a Fellow of the IEEE, a foreign member of the Royal Swedish Academy of Engineering Sciences, a Fellow of the International Federation of Automatic Control,
and a member of the Galilean Academy of Sciences, Letters and Arts in Padua.

Selected publications

  • Lindquist, A., & Picci, G.. Series in Contemporary Mathematics: vol. 1, Linear Stochastic Systems: A Geometric Approach to Modeling, Estimation and Identification. Springer-Verlag, Berlin Heidelberg. This book was translated into Chinese and published in two volumes by the Shanghai Scientific and Technical Publishers in 2018.
Textbooks:
Edited books:
  • Picci, G. & Valcher, M. E. eds.. A Tribute to Antonio Lepschy. Libreria Progetto, Padua.
  • Beghi, A., Finesso, L., & Picci, G. eds.. Mathematical Theory of Networks and Systems: Proceedings of the MTNS-98 Symposium Held in Padova, Italy, July, 1998, Il Poligrafo, Padua.
  • Bittanti, S. & Picci, G. eds.. NATO ASI Subseries F: vol. 153, Identification, Adaptation, Learning: The Science of Learning Models from Data. Springer-Verlag, Berlin Heidelberg.
Recent papers:
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