Prof. Jose C. Principe

Jose C. Principe, (M’83-SM’90-F’00) is Distinguished Professor of Electrical and Biomedical Engineering at the University of Florida, Gainesville, where he teaches advanced signal processing and artificial neural networks (ANN’s) modeling. He is BellSouth Professor and Founder and Director of the University of Florida Computational NeuroEngineering Laboratory (CNEL). He has been involved in biomedical signal processing, in particular the electroencephalogram (EEG), and the modeling and applications of adaptive systems. Dr. Principe is Editor in Chief IEEE Transactions on Biomedical Engineering, President Elect of the International Neural Network Society, and formal Secretary of the Technical Committee on Neural Networks of the IEEE Signal Processing Society. He is also a member of the Scientific Board of the Food and Drug Administration, and a member of the Advisory Board of the University of Florida Brain Institute. He has more than 90 publications in refereed journals, 10 book chapters, and over 190 confernce papers. He has directed 39 Ph.D. degree dissertations and 57 master degree theses.
   

Prof. Vladmir Vapnik

Professor Vapnik gained his Masters Degree in Mathematics in 1958 at Uzbek State University, Samarkand, USSR. From 1961 to 1990 he worked at the Institute of Control Sciences, Moscow, where he became Head of the Computer Science Research Department. He then joined AT&T Bell Laboratories , Holmdel, NJ, where he now continues as a Consultant, having been appointed Professor of Computer Science and Statistics at Royal Holloway in 1995.

Professor Vapnik has taught and researched in computer science, theoretical and applied statistics for over 30 years. He has published 6 monographs and over a hundred research papers. His major achievements have been the development of a general theory for minimizing the expected risk of losses using empirical data, and a new type of learning machine called Support Vector machine that possesses a high level of generalization ability. These techniques have been used to solve many pattern recognition and regression estimation problems and have been applied to the problems of dependency estimation, forecasting, and constructing intelligent machines.

He was one of the invited speakers at the Colloquium "The Importance of being Learnable" hosted by the Computer Learning Research Centre at Royal Holloway in September 1998. His current research is presented in his latest book "Statistical Learning Theory", ISBN No: 0-471-03003-1.

   

Prof. Peter Erdi

- Henry R. Luce Professor, and founding director of the Center for
Complex Studies at Kalamazoo College. Joint appointment with
Dept Physics and Dept. Psychology.
- Head of Department of Biophysics KFKI Research Institute for Particle
and Nuclear Physics of the Hungarian Academy of Sciences
- Permament guest professor Dept. History and Philosophy of Science,
Eötvös University, Budapest
- Co-directors of the Budapest Semester in Cognitive Science
- PhD and DSc: Hungarian Academy of Science
- Széchenyi Professor (1999-2002)
Books:
- Érdi P and Tóth J: Mathematical Models of Chemical Reactions. Manchester
Univ. Press., 1989. Princeton Univ. Press., 1989.;
- Arbib MA, Érdi P and Szentágothai J: Neural Organization: Structure,
Function Dynamics. MIT Press, A Bradford Book, 1997
Research Interests:
Computational Neuroscience; Complex Adaptive Networks
   

Prof. Walter Freeman

Walter J. Freeman (Fellow, IEEE) studied physics and mathematics at the Massachusetts Institute of Technology, English and philosophy at the University of Chicago, medicine at Yale University (M.D. 1954), internal medicine at Johns Hopkins University, and neurophysiology at the University of California, Los Angeles. He has taught brain science at the University of California, Berkeley, CA, since 1959, where he is Professor of the Graduate School. He is the author of Mass Action in the Nervous System (1975), Societies of Brains (1995), How Brains MakeUp Their Minds (1999), and Neurodynamics: An Exploration of Mesoscopic Brain Dynamics (2000).
   

Prof. Nik Kasabov

Unfortunately, Professor Nik Kasabov won´t be present to the event.
   

Prof. Xin Yao
Xin Yao (M’91–SM’96–F’03) received the B.Sc. degree from the University of Science and Technology of China (USTC), Hefei, the M.Sc. degree from the North China Institute of Computing Technologies (NCI), Beijing, and the Ph.D. degree in computer science from the USTC, in 1982, 1985, and 1990, respectively, all in computer science. He is currently a Professor of Computer Science and the Director of the Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA), University of Birmingham, U.K., and a Visiting Professor at four other universities in China and Australia. He was a Lecturer, Senior Lecturer, and an Associate Professor at University College, University of New South Wales, the Australian Defence Force Academy (ADFA), Canberra, Australia, between 1992–1999. He held Postdoctoral Fellowships from the Australian National University (ANU), Canberra, and the Commonwealth Scientific and Industrial Research Organization (CSIRO), Melbourne, between 1990 and 1992. His major research interests include evolutionary computation, neural network ensembles,global optimization, computational time complexity, and data mining. Dr.Yao is the Editor-in-Chief of the IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, an Associate Editor, and an Editorial Board Member of five other international journals, and the Chair of the IEEE Neural Networks Society Technical Committee on Evolutionary Computation. He is the recipient of the 2001 IEEE Donald G. Fink Prize Paper Award and has given more than 20 invited keynote and plenary speeches at various conferences. He has chaired/cochaired more than 25 international conferences in evolutionary computation and computational intelligence, including CEC 1999, PPSN VI 2000, CEC 2002, and PPSN 2004.
   

Prof. Anthony Bell

Anthony J. (Tony) Bell received the M.A. degree in computer science and philosophy from the University of St. Andrews, Scotland, in 1987 and the Ph.D. degree in artificial intelligence from the Free University of Brussels, Belgium, in 1993. Since 1990, he has been associated with the Computational Neurobiology Laboratory of the Salk Institute, San Diego, as a visitor or postdoctoral researcher, and has also worked at Interval Research, Palo Alto, CA.
   

Prof. Kazuyuki Aihara

Kazuyuki Aihara received the B.E. degree in electrical engineering in 1977 and the Ph.D. degree in electronic engineering 1982 from the University of Tokyo, Tokyo, Japan. Currently, he is Professor in the Department of Complexity Science and Engineering and Department of Mathematical Engineering and Information Physics, the University of Tokyo. He is also Chairman of the Biochaos Research Committee in the Japan Electronic Industry Development Association. His research interests include mathematical modeling of biological neurons, parallel distributed processing with chaotic neural networks, and time series analysis of chaotic data.