Brian Anderson

Award Received:

IEEE CSS Hendrik W. Bode Lecture Prize

Date Awarded:

1992

Biography

Brian Anderson is Distinguished Professor at the Australian National University and Distinguished Researcher in National ICT Australia. His interests are in currently in formation control, sensor networks and econometric modelling. His past contributions have been in other areas of control as well as circuit theory, signal processing and telecommunications.

He was born in Sydney, Australia, and received his undergraduate education at the University of Sydney, with majors in pure mathematics and electrical engineering. He subsequently obtained a PhD degree in electrical engineering from Stanford University. Following completion of his education, he worked in industry in Silicon Valley and served as a faculty member in the Department of Electrical Engineering at Stanford. He was Professor of Electrical Engineering at the University of Newcastle, Australia from 1967 until 1981.

He is a Fellow of the IEEE, IFAC, Royal Society London, Australian Academy of Science, Australian Academy of Technological Sciences and Engineering, Honorary Fellow of the Institution of Engineers, Australia, and Foreign Associate of the US National Academy of Engineering. He holds doctorates (honoris causa) from the Université Catholique de Louvain, Belgium, Swiss Federal Institute of Technology, Zürich, and the universities of Sydney, Melbourne, New South Wales and Newcastle in Australia. He served as President of the International Federation of Automatic Control from 1990 to 1993 and as President of the Australian Academy of Science between 1998 and 2002. His awards include the IEEE Control Systems Award of 1997, the 2001 IEEE James H Mulligan, Jr Education Medal, and the Guillemin-Cauer Award, IEEE Circuits and Systems Society in 1992 and 2001, the Bode Prize of the IEEE Control System Society in 1992, the Senior Prize of the IEEE Transactions on Acoustics, Speech and Signal Processing in 1986, and other best paper awards.

Citation:

For revealing fundamental feedback properties in scholarly papers on optimal and adaptive filtering and for seminal expository textbooks and monographs