2001 NNC Meritorious Service Award
Please join me to congratulate Prof. James Bezdek on his year 2001 Meritorious Service Award.

Almost singlehandedly, Jim Bezdek brought fuzzy systems into the NNC. When he was first contacted about doing this, he said "tell me what to do and I'll do it". As a result, Jim was the founding editor of the IEEE Transactions on Fuzzy Systems. He wrote the proposal for the publication and ushered it through the NNC and IEEE Processes. He also organized the first FUZZ-IEEE. This is currently the largest most prestigious conference in the area. IEEE TFS is the premier fuzzy journal in the world. Jim, of course, went on to serve the NNC as VP for conferences and, later, the President of the NNC. He is also a great word smith. The term "FUZZ-IEEE" was coined by Jim. He put the "Computational Intelligence" in WCCI. Prior to his suggestion - the name was the IEEE World Congress on Intelligent Systems. CI is a much better description of the field and has been adopted world wide as the field of neural networks, fuzzy systems & evolutionary computation. He is well deserving of this award.

Mary Lou Padgett, Awards Committee Chair

2001 NNC Neural Networks Pioneer Award
Please join us to congratulate Prof. David Rumelhart and James McCelland on their year 2001 Neural Networks Pioneer Award.

David E. Rumelhart has made many contributions to the formal analysis of human cognition, working primarily within the frameworks of mathematical psychology, symbolic artificial intelligence, and parallel distributed processing. He also admired formal linguistic approaches to cognition and explored the possibility of formulating a formal grammar to capture the structure of stories.

Rumelhart obtained his undergraduate education at the University of South Dakota, receiving a B.A. in psychology and mathematics in 1963. He studied mathematical psychology at Stanford University, receiving his Ph. D. in 1967. From 1967 to 1987 he served on the faculty of the Department of Psychology at the University of California, San Diego. In 1987 he moved to Stanford University, serving as Professor there until 1998. He has become disabled by Pick's disease, a progressive neurodegenerative illness, and now lives with his brother in Ann
Arbor, Michigan.

Rumelhart developed models of a wide range of aspects of human cognition, ranging from motor control to story understanding to visual
letter recognition to metaphor and analogy. He collaborated with Don Norman and the LNR Research Group to produce "Explorations in Cognition" in 1975 and with Jay McClelland and the PDP Research Group to produce "Parallel Distributed Processing: Explorations in the Microstructure of Cognition" in 1986. He mastered many formal approaches to human cognition, developing his own list processing language and formulating the powerful back-propagation learning algorithm for training networks of neuron-like processing units. Rumelhart was elected to the National Academy of Sciences in 1991 and received many prizes, including a MacArthur Fellowship, the Warren Medal of the Society of Experimental Psychologists, and the APA Distinguished Scientific Contribution Award.

Rumelhart articulated a clear view of what cognitive science, the discipline, is or ought to be. He felt that for cognitive science to be a science, it would have to have formal theories --- and he often pointed to linguistic theories, as well as to mathematical and computational models, as examples of what he had in mind.

James L. McClelland's model of memory consolidation between the hippocampus and the neocortex ... has inspired much more sophisticated neuroscience research than in the past (more influenced by solid systems theory), and, as a computational architecture, it addresses the important issue of "syncretism" more effectively than the present work in engineering.
In addition, his role in the PDP group and their books is well-documented.

Mary Lou Padgett, Awards Committee Chair
Gary G. Yen, Neural Networks Technical Committee Chair

2001 NNC Fuzzy Systems Pioneer Award
Please join us to congratulate Prof. James Bezdek on his year 2001 Fuzzy Systems Pioneer Award.

James C. Bezdek. In the early 70's Professor Bezdek developed the theory of fuzzy C-means (FCM) clustering. In his FCM theory Professor Bezdek laid a solid theoretical foundation for the application of fuzzy theory to pattern recognition, reasoning, and neural-fuzzy systems. In addition to its theoretical value, the FCM theory offered researchers and engineers with a systematic procedure for developing pattern recognition systems, which had not been previously available. Since the seminal work of Professor Zadeh on fuzzy sets and fuzzy logic, the FCM theory has been widely recognized as the most important fuzzy theory relative to the application area of pattern recognition.
This has led to numerous successful applications in many areas, including control, information management, intelligent processing and manufacturing, biomedical engineering, computer vision, and more recently, e-commerce systems. It is through Professor Bezdek's pioneering work on FCM that we have seen wide acceptance of fuzzy theory as one of the major scientific and engineering disciplines,
which is particularly evidenced in pattern recognition.

For more than three decades, Professor Bezdek has been extremely active in research on fuzzy systems and has tirelessly disseminated the fuzzy theory, in particular, neural-fuzzy systems for pattern recognition. Professor Bezdek's contributions have been recognized world wide: He has given countless lectures as a distinguished lecturer and key/planary speeches in major international forums. His books, papers, lectures, and speeches have inspired many new developments. Although having an extremely busy schedule, Professor Bezdek is always willing to guide younger researchers and students in their research projects, which has helped nurture new generations of outstanding researchers and engineering in the fuzzy systems community.

It is through Professor Bezdek's pioneering efforts in serving the research community that we have experienced the great success of fuzzy theory in pattern recognition and intelligent systems. In addition to his many groundbreaking research activities, Professor Bezdek has been serving the research community with exceptional dedication and initiatives. Professor Bezdek has held numerous society office positions. Most notably, Professor Bezdek was the founding Editor-in-Chief of the International Journal of Approximate Reasoning, and the founding Editor-in-Chief of the IEEE Transactions on Fuzzy Systems, which has probably been the premier journal on fuzzy research ever since its inaugural issue in 1993; the President of IEEE Neural Network Council; and was the general chair of the first IEEE International Conference on Fuzzy Systems. In addition, Professor Bezdek has been on editorial/advisory boards of over 20 international journals and a guest editor for numerous special issues on neural-fuzzy system for pattern recognition and intelligent systems. Professor Bezdek was a recent recipient of the IEEE Third Millennium Medal, and has been a fellow of the IEEE since 1992.

Mary Lou Padgett, Awards Committee Chair
Valerie V. Cross, Fuzzy Systems Technical Committee Chair

2001 NNC Evolutionary Computation Pioneer Award
Please join us to congratulate Prof. Michael Conrad on his year 2001 Evolutionary Computation Pioneer Award.

Michael Conrad is one of the most deserving people for the IEEE NNC EC Pioneer Award. His illustrious career in evolutionary computation dates back to the late 1960s, where he was one of the first to simulate an open-ended ecosystem on a computer. This was perhaps the first or second real attempt at what we would now call "artificial life." His work was published in the Journal of Theoretical Biology. Following shortly after his Ph.D. in 1970, he published on the relationship between evolutionary learning and neural circuit learning, making himself one of the first people to write explicitly on this connection. He later, in 1983, became the coauthor of the first journal paper that explicitly couples evolutionary algorithms and neural networks (this paper is reprinted in Evolutionary Computation: The Fossil Record). This achievement alone would merit the pioneer award. Prof. Conrad has supervised many students in evolutionary computation (including Prof. Mateen Rizki, associate editor, IEEE Trans EC) and has had a lasting effect on the field. He took a leading role in bringing evolutionary algorithms to the forefront of biological modeling, particularly in his efforts as co-managing editor of the journal BioSystems (Elsevier). I am not aware of the exact date of his taking this position, but I believe that it is well before the 15-year mark that is required for a contribution to be relevant to the pioneer award. Prof. Conrad also introduced the concept of bootstrapping on adaptive landscapes in the 1970s, where local stagnation is overcome by a "extra-dimensional bypass" which might be the result of new genes.

Few people have made the breadth of contribution to evolutionary computation that Michael Conrad has. I sincerely hope that he receives the recognition of the IEEE NNC in this important acknowledgment of his work from 1969-1985.

Mary Lou Padgett, Awards Committee Chair
Xin Yao, Evolutionary Computation Technical Committee Chair

2001 NNC Neural Networks Outstanding Paper Award
Please join us to congratulate Prof. Yasuo Matsuyama on his year 2001 Neural Networks Outstanding Paper Award.

Yasuo Matsuyama,
"Multiple Descent Cost Competition: Restorable Self-Organization and Multimedia Information Processing,"
IEEE TNN, 9(1), January 1998, pp. 106-122.

Mary Lou Padgett, Awards Committee Chair
Jacek Zurada, TNN Editor-in-Chief
Gary G. Yen, Neural Networks Technical Committee Chair

2001 NNC Fuzzy Systems Outstanding Paper Award
Please join us to congratulate Prof. Joongseon Joh, Ye-Haw Chen and Reza Langari on their year 2001 Fuzzy Systems Outstanding Paper Award.

Joonseon Joh, Ye-Haw Chen, and Reza Langari,
"On the Stability of Issues of Linear Tagaki-Sugeno Fuzzy Models"
IEEE TFS, 6(3), August 1998, pp. 402-410.

Mary Lou Padgett, Awards Committee Chair
Jim Keller, TFS Editor-in-Chief
Valerie V. Cross, Fuzzy Systems Technical Committee Chair

2001 NNC Evolutionary Computation Outstanding Paper Award
Please join us to congratulate Prof. Agoston Endre Eiben and Zbigniew Michalewicz on their year 2001 Evolutionary Computation Outstanding Paper Award.

Agoston Endre Eiben, Robert Hinterding, and Zbigniew Michalewicz,
"Parameter Control in Evolutionary Algorithms,"
IEEE TEC, 3(2), July 1999, pp. 124-141.

Mary Lou Padgett, Awards Committee Chair
David Fogel, TEC Editor-in-Chief
Xin Yao, Evolutionary Computation Technical Committee Chair

2001 IEEE NNC Student Summer Research Grant Recipients
I am happy to inform you that the Committee on the IEEE NNC Student Summer Research Grants has completed its review and recommendations.
The panel was invited by me, the NNC Education Activities Chair, to review and rank all proposals. We have received more excellent proposals than the allocated budget can accommodate. The students that have been chosen for support are listed (in alphabatical order) as follows:

     Ivana Ljubic
     Phayung Meesad
     Ganesh K. Venayagamoorthy
     Khurram Waheed

On behalf of the IEEE Neural Networks Council, I want to extend my congratulations to all of you. The NNC is certain this Summer Research
Program is a great investment in the future of computational intelligence. I regret that we are not able to support all of those who applied this time. I
would like to thank all of you for applying to the program, and encourage those who did not succeed this time to apply for future NNC opportunities.

Karen G. Haines, Education Activities Chair

2001 IEEE NNC Student Travel Grant Recipients- CEC 2001
The Committee on IEEE NNC Student Travel Grants provided recommendations for those students receiving this year's IEEE NNC Student Travel Grants. We received many applications and our budget was limited. The students that are eligible for support are shown in the list which follows. If your name is not on this list, you did not receive an award. Our policy is to support all student authors by the amount of $800US. However, if you live in the city which is hosting the conference, your travel grant award is limited to cost of early student registration. All travel support and travel awards will be processed after the respective conference. To receive the travel grant, recipients must:

We thank the IEEE Neural Networks Council for supporting the student travel grant program. This program is an investment in the future of computational intelligence areas represented at all IEEE NNC sponsored conferences. We are really sorry we are not able to support the travel expenses for all of you who applied. We are looking forward to seeing you all at the conference.

IEEE NNC Student Travel Grant Selection Committee

CEC 2001
     Si-Duo Chen
     Artur Chorazyczewski
     Francisco Fernández
     Carlos Fernandes
     Cindy Goh
     Tao-Yuan Huang
     Koh Giok Khoo
     Eik Fun Khor
     Sun Kim
     Yong Seog Kim
     Michael Kirley
     Giridhar Kumaran
     Chong Lee
     Jingpeng Li
     Michael Lones
     Benjamin Rubinstein
     Tom Smith
     Chuan-Kang Ting
     Fangming Zhu

2001 IEEE NNC Student Travel Grant Recipients- IJCNN 2001
The Committee on IEEE NNC Student Travel Grants provided recommendations for those students receiving this year's IEEE NNC Student Travel Grants. We received many applications and our budget was limited. The students that are eligible for support are shown in the list which follows. If your name is not on this list, you did not receive an award. Our policy is to support all student authors by the amount of $800US. However, if you live in the city which is hosting the conference, your travel grant award is limited to cost of early student registration. All travel support and travel awards will be processed after the respective conference. To receive the travel grant, recipients must:

IEEE NNC Student Travel Grant Selection Committee

IJCNN 2001
     Moumen Ahmed
     Paulo E. M. Almeida
     Remus Brad
     Macarie Breazu
     Lorenzo Brignone
     Cesar Augusto Casas
     Sooyong Choi
     Erika Cota
     Simona Doboli
     Ming Dong
     Thomas Frontzek
     Suryakanth V. Gangashetty
     Adam Gaweda
     Thomas Hanselmann
     Harlan Harris
     Orlando De Jesus
     Sasa Jevtic
     Jae-Byung Jung
     Junaid A. Khan
     KyunByoung Ko
     Mykola Lysetskiy
     Mahmood Minhas
     Eiji Mizutani
     Luis Monzon
     Hassan Heidari Namarvar
     Vassilis Plagianakos
     M. Rukonuzzaman
     Thaddeus Shannon
     Jie Shao
     Mia Nazmul Haque Siddique
     Renata Smolikova
     Rainer Spiegel
     Min Su
     Kenji Suzuki
     Antonio Ulloa
     Frans van den Bergh
     Nicolaas van der Merwe
     Mark Wachowiak
     Pew-Thian Yap
     James Young
     Jian Zhang
     Yilu Zhang

New Book: Hybrd Neural Systems, Springer-Verlag, March 2000
by Stefan Wermter and Ron Sun (eds.)

The aim of this book is to present a broad spectrum of current research in hybrid neural systems, and advance the state of the art in neural networks and artificial intelligence. Hybrid neural systems are computational systems which are based mainly on artificial neural networks but which allowa symbolic interpretation or interaction with symbolic components. This book focuses on the following issues related to different typesof representation: How does neural representation contribute to the success of hybrid system? How does symbolic representation supplement neural representation? How can these types of representation be combined? How can we utilizetheir interaction and synergy? how can we develop neural and hybrid systems for new domains? What are the strengths and weaknesses of hybrid neural techniques? Are current principles and methodologies in hybrid neural systems useful? How can they be extended? What will be teh impact of hybrid and neural techniques in the future?

Hybrid neural systems can be ordered from Springer-Verlag by using the on-line Order form.

New Book: Advances in Neural Information Processing Systems 12, MIT Press, June 2001
by Sara A. Solla, Todd K. Leen, and Klaus-Robert Müller (eds.)
http://mitpress.mit.edu/book-home.tcl?isbn=0262194503

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

New Book: Learning and Soft Computing, Support Vector Machines, Neural Networks and Fuzzy Logic Models, MIT Press, May 2001
by Vojislav Kegman
http://mitpress.mit.edu/book-home.tcl?isbn=0262112558

This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.

New Book: Evolutionary Robotics: the Biology, Intelligence, and Technology of Organizing Machines, MIT Press, May 2001
by Stefano Nolfi and Dario Floreano
http://mitpress.mit.edu/book-home.tcl?isbn=0262140705
Evolutionary robotics is a new technique for the automatic creation of autonomous robots. Inspired by the Darwinian principle of selective
reproduction of the fittest, it views robots as autonomous artificial organisms that develop their own skills in close interaction with the environment and without human intervention. Drawing heavily on biology and ethology, it uses the tools of neural networks, genetic algorithms,
dynamic systems, and biomorphic engineering. The resulting robots share with simple biological systems the characteristics of robustness, simplicity, small size, flexibility, and modularity.

In evolutionary robotics, an initial population of artificial chromosomes, each encoding the control system of a robot, is randomly created and put
into the environment. Each robot is then free to act (move, look around, manipulate) according to its genetically specified controller while its performance on various tasks is automatically evaluated. The fittest robots then "reproduce" by swapping parts of their genetic material with small random mutations. The process is repeated until the "birth" of a robot that satisfies the performance criteria.

This book describes the basic concepts and methodologies of evolutionary robotics and the results achieved so far. An important feature is the
clear presentation of a set of empirical experiments of increasing complexity. Software with a graphic interface, freely available on a Web page
(http://gral.ip.rm.cnr.it/evorobot/simulator.html), allows the reader to replicate and vary (in simulation and on real robots) most of the
experiments.

New Book: Fuzzy Logic Techniques for Autonomous Vehicle Navigation, Springer-Verlag, 2001
by Driankov, D. and Saffiotti, A. (Eds)
http://www.aass.oru.se/Living/FLAR/Book2001/

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.