This page is to honor Experts in the field. The names are listed alphabetically,
along with their areas of expertise and contact Information.

This list is by no means exhaustive, and will always be a work in progress.

We apologize in advance from all great minds that were left out and encourage you to contact us if you know of any.

Research from Prof. Lendaris in Portland State University includes development and application of massively parallel computation methodology known as neural networks or connectionist networks. Methodology development focuses on the idea of matching the structure/architecture of a network to structural relations in data of problem context. This requires developing a common mechanism for describing structure in data and structure of a network so a matching process can be possible. One approach is based on a knowledge representation formalism known as conceptual structures, and another is based on a structure representation formalism called general systems methodology (GSM) notation. Applications being pursued include pattern recognition and implementation of selected database/expert system operations. In the planning stage are control applications. Future work includes collaboration with other faculty in developing analog/digital VLSI implementations of neural networks.

LOTFI A. ZADEH is a Professor in the Graduate School, Computer Science Division, Department of EECS, University of California, Berkeley. In addition, he is serving as the Director of BISC (Berkeley Initiative in Soft Computing).
His seminal paper on Fuzzy Sets (1965) provided a basis for a qualitative approach to the analysis of complex systems in which linguistic rather than numerical variables are employed to describe system behavior and performance. In this way, a much better understanding of how to deal with uncertainty may be achieved, and better models of human reasoning may be constructed.

Paolo is an Italian IT specialist with over 20 years of experience in the field. Currently he is working at a large Italian Bank, in Rome, responsible for J2EE Architecture and System Integration. His interested in Neural Networks began in 1989, when he started to study the possibility to use the neural networks outside the academic world, making them suitable also for the industrial market. Feeling the necessity of a different approach, the focus of his activity in the last five years was to address issues in the development of a neural network framework based on the last available technologies, with particular emphasis to important features like portability, scalability, extensibility, modularity, etc. The result of that work is Joone, an Open Source neural network framework written in Java.

Dr. Susan K. McConnell is Professor of Humanities and Sciences in the Department of Biological Sciences at Stanford University. She received her A.B. degree Summa Cum Laude from Harvard and Radcliffe Colleges in 1980. In 1987 she earned the Ph.D. degree in Neurobiology from Harvard University, where she worked with Dr. Simon LeVay. Following postdoctoral training with Dr. Carla Shatz at the Stanford University School of Medicine, McConnell joined the Stanford faculty in 1989. McConnell has been awarded a number of research fellowships including the Searle Scholar award, Pew Scholar in the Biomedical Sciences, McKnight Scholar, Alfred P. Sloan Research Fellow, National Science Foundation Presidential Young Investigator, and McKnight Investigator awards. She has received recognition for her research and teaching skills, as evidenced by awards that include the Society for Neuroscience Young Investigator Award, the Marcus Singer Award in developmental biology, a National Science Foundation Presidential Faculty Fellowship, a Terman Fellowship, and the Walter J. Gores Award for Excellence in Teaching and the Hoagland Prize for Undergraduate Teaching at Stanford University. McConnell's primary research goal is to understand how neurons in the developing brain are produced, assigned specific phenotypes, and wired together into functional circuits. Her research has contributed to our understanding of how neurons are produced from multipotent progenitor cells and how these neurons migrate into appropriate positions within the developing brain.