In Memoriam- Walter J. Karplus


On November 11, 2001, the Neural Network Council (NNC) lost one of its pioneers. Walter J. Karplus passed away that day at the age of 74 after a brief struggle with lung cancer. He is survived by his wife, Takako, and two children, Maya and Tony.

Dr. Karplus was born in Vienna, Austria. He received the B.E.E. degree from Cornell University, Ithaca, NY in 1949 and the M.S. and Ph.D. degrees from the University of California, Los Angeles, (UCLA) in 1951 and 1955, respectively. He joined the UCLA faculty in 1955 and served as Chairman of the Computer Science Department from 1972 to 1979. He also held positions as Interim Dean of the UCLA Henry Samueli School of Engineering and Applied Science, Head of the Computer Simulation Laboratory, and Director of teh Center for Experimental Computer Science.

During his more than 40 years of distinguished service at UCLA, he made many contributions to computer science. He successfully employed virtual reality to allow doctors to observe blood flows through aneurysms in the human brain. He also used virtual audio to sort out critical information in noisy environments, such as the NASA mission control room. In recent years, his research emphasized the modeling, simulation, and control of physical and biological systems using massive parallelism, neural networks, and virtual reality. This naturally led to his involvement with the IEEE NNC.

Walter Karplus, who was a Life Fellow of the IEEE, served as President of teh IEEE NNC in 1995 and 1996. The Council thrived and matured under his leadership. He initiated a number of education programs that resulted in strong student participation in the fields of neural networks, fuzzy systems, evolutionary computation and their applications.

In 1996, he conducted a successful review of teh NNC by the IEEE Technical Activities Board (TAB), which brought much recognition to the Council and its activities while laying the foundation for its future. Walter will be remembered as a visionary leader with strong interpersonal skills. His demeanor was quite, logical, and reasoned, while at the same time firm and resolute.

Walter had a strong desire for the NNC to become a Society, bringing this issue to the attention of TAB on numerous occassions. He would have been pleased to know that his dream finally came tue on November 17, 2001 when TAB endorsed the formation of the Neural Network Society. Today, members of the IEEE and the engineering and scientific community at large can enjoy the fruits of his labor.

Clifford Lau, President 1999-2000

IEEE Fellows- Classs of 2002
<<Picture is not available>>
Hamid R. Berenji, Intelligent Inference Systems Corp, Moffett Field, CA
For contributions to the development of fuzzy reinforcement  learning theory


Bor-Shen Chen, National Tsing Hua University, Hsinchu, Taiwan
For contributions to fuzzy control theory and its applications

Bor-Sen Chen received the B.S. degree from Tatung Institute of Technology, Taipei, Taiwan, R.O.C., the M.S. degree from National Central University, Chungli, Taiwan, and the Ph.D. degree from the University of Southern California, Los Angeles, in 1970, 1973, and 1982, respectively. He was a Lecturer, Associate Professor, and Professor at Tatung Institute of Technology from 1973 to 1987. He is currently a Professor with National Tsing Hua University, Hsinchu, Taiwan. His current research interests are in control engineering and signal processing. Dr. Chen received the Distinguished Research Fellow of the National Science Council of Taiwan four times. He is a Research Fellow of the National Science Council of Taiwan and holds the Excellent Scholar Chair in Engineering. He received the Automatic Control Medal from the Automatic Control Society of Taiwan in 2001.


Donald H. Kraft, Louisiana State University, Baton Rouge, LA
For contributions to text retrieval via fuzzy set theory and  genetic algorithms.

Donald H. Kraft holds the BSIE, MSIE, and Ph.D. degrees in industrial engineering, all from Purdue University.  He has been on the faculty at the University of Maryland, and been a visiting faculty member at the University of California, Berkeley, Indiana University, and the University of California, Los Angeles.  He has been a professor of computer science at Louisiana State University for twenty-five years and is now an adjunct professor of library and information science at LSU.  Professor Kraft is the Editor of the Journal of the American Society for Information Science and Technology (JASIST), an Associate Editor of the IEEE Transactions on Fuzzy Systems (TFS), and is President of the American Society for Information Science and Technology (ASIST).  He was Chair of the Association for Computing Machinery (ACM) Special Interest Group on Information Retrieval (SIGIR) International Conference on Research and Development in Information Retrieval, held September 9-13, 2001 in New Orleans, Louisiana; and is the Co-Chair of the North American Fuzzy Information Processing Society (NAFIPS) conference, to be held in New Orleans in June 2002.


Majid Ahmadi, University of Windsor, Windsor, ON Canada
For contributions to the design of digital filters, and to pattern  recognition and image restoration.

Majid Ahmadi received his B.Sc. degree in electrical engineering from Arya Mehr University in Tehran, Iran, and Ph.D. in electrical engineering from Imperial college of London University, London, U.K., in 1971 and 1977, respectively. He has been with the Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada, since 1980, currently as Professor and Associate Director for Research Center for Integrated Microsystems. His research interests include digital signal processing, machine vision, pattern recognition, neural network architectures, applications and VLSI implementation and has published over 300 articles in these areas. He has co-authored the book Digital Filtering in 1-D and 2-Dimensions, Design and Applications (New York:Plenum,1989) . Dr. Ahmadi is an Associate Editor for the Journal of Pattern Recognition, Journal of Circuits, Systems and Computers, and the International Journal of Computers in Electrical Engineering, and is the IEEE-CAS representative on the Neural Network Council, and Past Chair of the IEEE Circuits and Systems Neural Systems Applications Technical Committee. He was a recipient of an Honorable Mention Award from the Editorial Board of the Pattern Recognition Journal in 1992, and the Distinctive Contributed Paper Award from the Multiple-Valued Logic Technical Committee of the IEEE Computer Society in 2000.He is a Fellow of the IEE, U.K and Fellow of the IEEE.

New Book: Adaptive Modelling, Estimation and Fusion from Data, Springer-Verlag, 2002 (ISBN 3-540-42686-8)
by Chris Harris, Xia Hong, Quiang Gan
http://www.springer.de/cgi/svcat/bag_generate.pl?ISBN=3-540-42686-8

This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive
mathematical framework. After introducing the basic theory of data based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency. The book is aimed at researchers and scientists in time series modeling, empirical data modelling, knowledge discovery, data mining, and data fusion.
The goal of autonomous mobile robotics is to build and control physical systems which can move purposefully and without human intervention in real-world environments which have not been specifically engineered for the robot. The development of techniques for autonomous mobile robot operation constitutes one of the major trends in the current research and practice in modern robotics. This volume presents a variety of fuzzy logic techniques which address the challenges posed by autonomous robot navigation. The focus is on four major problems: how to design robust behavior-producing control modules; how to coordinate the activity of several independent behaviors; how to use data from sensors for the purpose of modeling the environment; and how to integrate high-level reasoning and low-level behavior execution. In this volume state-of-the-art fuzzy logic solutions are presented and their pros and cons are discussed in detail based on extensive experimentation on real mobile robots.