B. Ross Barmish

Award Received:

IEEE CSS Hendrik W. Bode Lecture Prize

Date Awarded:

2013

Biography

B. Ross Barmish received the Bachelor's degree in Electrical Engineering from McGill University in 1971. In 1972 and 1975 respectively, he received the M.S. and Ph.D. degrees, both in Electrical Engineering, from Cornell University. From 1975 to 1978, he served as Assistant Professor of Engineering and Applied Science at Yale University. From 1978 to 1984, he was as an Associate Professor of Electrical Engineering at the University of Rochester and in 1984, he joined the University of Wisconsin, Madison, where he is currently Professor of Electrical and Computer Engineering. From 2001 to 2003, he was with the Department of Electrical Engineering and Computer Science at Case Western Reserve University, where he served as Department Chair while holding the endowed Nord Professorship. Over the years, he has been involved in a number of IEEE Control Systems Society activities such as associate editorships, conference chairmanships, the Board of Governors and prize paper committees. He has also served as a consultant for a number of companies and is the author of the textbook New Tools for Robustness of Linear Systems, Macmillan, 1994. Professor Barmish is a Fellow of both the IEEE and IFAC for his contributions to the theory of robustness of dynamical systems. He received the Best Paper Award for Journal Publication in Automatica, covering a three-year period, on two consecutive occasions from the International Federation of Automatic Control. He has also given a number of plenary lectures at major conferences. While his earlier work concentrated on robustness of dynamical systems, his current research, the topic of this Bode lecture, concentrates on building a bridge between feedback control theory and trading in complex financial markets.

Citation:

For fundamental contributions to the analysis of systems with parametric uncertainty and to probabilistic robustness, and for contributions to the design of stock-trading algorithms that are robust to market variability