Professor Asim Roy

The PhysOrg article Professor Finally Publishes Controversial Brain Theory said

In the late ’90s, Asim Roy, a professor of information systems at Arizona State University, began to write a paper on a new brain theory. Now, 10 years later and after several rejections and resubmissions, the paper Connectionism, Controllers, and a Brain Theory has finally been published in IEEE Transactions on Systems, Man, and Cybernetics — Part A: Systems and Humans.
 
However, Roy’s controversial ideas on how the brain works and learns probably won’t immediately win over many of his colleagues, who have spent decades teaching robots and artificial intelligence (AI) systems how to think using the classic connectionist theory of the brain. Connectionists propose that the brain consists of an interacting network of neurons and cells, and that it solves problems based on how these components are connected. In this theory, there are no separate controllers for higher level brain functions, but all control is local and distributed fairly equally among all the parts.
 
In his paper, Roy argues for a controller theory of the brain. In this view, there are some parts of the brain that control other parts, making it a hierarchical system. In the controller theory, which fits with the so-called computational theory, the brain learns lots of rules and uses them in a top-down processing method to operate. In 1997, IBM’s Deep Blue computer, which famously defeated world chess champion Garry Kasparov, operated based on countless rules entered by its programmers.

Asim Roy, Ph.D. is Professor of Information Systems at Arizona State University. He earned his B.E. in Mechanical Engineering from Calcutta University, India, his M.S. in Operations Research from Case Western Reserve University, Cleveland, Ohio, and his Ph.D. in Operations Research from University of Texas at Austin. He also studied Industrial Engineering at Rutgers University, New Brunswick, New Jersey. He has been a Visiting Scholar at Stanford University, visiting Professor David Rumelhart in the Psychology Department, and a Visiting Scientist at the Robotics and Intelligent Systems Group at Oak Ridge National Laboratory, Oak Ridge, Tennessee.
 
Asim has been the Letters Editor of IEEE Transactions on Neural Networks and has served on organizing committees of many scientific conferences. He was the Program Chair for the ORSA/TIMS (Operations Research Society of America / The Institute of Management Sciences) National meeting in Las Vegas and the General Chair of the ORSA/TIMS National meeting in Phoenix.
 
His research interests are in brain-like learning, neural networks, machine learning, data mining, pattern recognition, prediction and forecasting, intelligent systems and nonlinear multiple objective optimization. His research has been published in Management Science, Decision Sciences, Mathematical Programming, Financial Management, Neural Networks, Neural Computation, Naval Research Logistics, ORSA Journal on Computing, IEEE Transactions on Neural Networks, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Systems, Man and Cybernetics and other journals.
 
Asim designed and developed the software system IFPS/OPTIMUM that pioneered the idea of incorporating optimization tools in financial and planning languages for managerial use. It has been used by hundreds of corporations worldwide for financial, corporate, and production planning. The system had saved many companies hundreds of millions of dollars. Following in its footsteps, such optimization systems are now widely available with spreadsheet systems such as Excel and Lotus 1–2-3.
 
He has recently published a new theory of the brain that postulates that there are parts of the brain that control other parts and thus control theoretic principles can be used to design and construct systems similar to the brain. This new theory invalidates the current dominant theory of the brain called “Connectionism” that has been widely used for the last 50 years. His work has been described as pioneering by distinguished scholars in the field. He has been invited to many national and international conferences for plenary talks and for tutorials, workshops and short courses on his new learning theory and methods.
 
Asim authored Artificial Neural Networks – A Science in Trouble and coauthored An algorithm to generate radial basis function (RBF)-like nets for classification problems, A polynomial time algorithm for the construction and training of a class of multilayer perceptrons, The Optimal Cost Chromatic Partition Problem for Trees and Interval Graphs, A Polynomial Time Algorithm for Generating Neural Networks for Pattern Classification: Its Stability Properties and Some Test Results, Extending planning languages to include optimization capabilities, and End-user optimization with spreadsheet models. He holds patent Pattern classification using linear programming.
 
Asim is listed in Who’s Who in America, Who’s Who in the World, Who’s Who in American Education, and Who’s Who in Industry and Finance, among others. He is on the Editorial Board of Neural Information Processing – Letters and Reviews.