Roger A. Browse, Queen’s University
Associate Professor
Computing and Information Sciences
Kingston, Ontario
browse@cs.queensu.ca
Office:
(613) 533-6000 ext. 36069
Expert In
Bio/Research
Dr. Browse carries out research in the area of human-machine interaction and virtual reality. His primary interest is in quantifying the performance improvements that accompany the introduction of advanced graphic display capabilities. For the purpose of entertainment, there is a great importance...
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Bio/Research
Dr. Browse carries out research in the area of human-machine interaction and virtual reality. His primary interest is in quantifying the performance improvements that accompany the introduction of advanced graphic display capabilities. For the purpose of entertainment, there is a great importance placed on the subjective impression of the reality of graphic displays. For other applications such as CAD/CAM, robotic teleoperation, and the use of virtual reality in medical applications, the most important aspect is the accuracy of the operator's understanding of the geometric structure that is being portrayed. Dr. Browse is currently experimenting with a variety of graphic rendering parameters, stereographic displays, and displays that update in response to the head position of the viewer.
Dr. Browse also conducts research in the area of neural networks. Neural networks are a particular form of parallel processing that is inspired by the way biological systems are structured and operate. Neural network systems have been remarkably successful in solving problems for which example solutions exist, because automated learning is an integral part of the operation of neural networks. Dr. Browse's primary interests are in the development of modular neural systems, and in the application of advanced search techniques such as genetic algorithms in the determination of the modular structure of a neural network.
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Dr. Browse also conducts research in the area of neural networks. Neural networks are a particular form of parallel processing that is inspired by the way biological systems are structured and operate. Neural network systems have been remarkably successful in solving problems for which example solutions exist, because automated learning is an integral part of the operation of neural networks. Dr. Browse's primary interests are in the development of modular neural systems, and in the application of advanced search techniques such as genetic algorithms in the determination of the modular structure of a neural network.
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