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Research Group Founders

 

Mr Sean Howard     
Industry Fellow and Project Sponsor


Sean Howard is an Australian entrepreneur and co-founder of OzEmail (along with Malcolm Turnbull and Trevor Kennedy) - at one time Australia's largest Internet company.  In the 1980s Howard developed the email service, Microtex. He also founded Australian Personal Computer, Australia's top-selling computer magazine.  In 2000 Howard joined the board of the telco Optus. As of 2005 he was a non-executive director of the WebCentral Group, a web and application hosting company. Sean joins the UQ Fluid Analogies group with a wealth of industry experience and a deep passion for understanding and modelling the mind.
 

Dr Scott Bolland
Senior Research Fellow

Scott's interest for computational modelling began over 20 years ago, although the opportunities for studying Cognitive Science formally did not exist until much later.  In 1993, Scott officially started a Cognitive Science degree at the University of Queensland, for which he received a University Medal for academic excellence.  For his Honour's project, Scott implemented a java based version of the Copycat program (a computational model of analogy-making and high-level perception) that provided him with a deep appreciation of the issues involved in modelling high-level cognition.  For his PhD, Scott continued this line of work, developing the Fluid Analogies Engine (FAE) - a generic model of high-level cognition, capable of problem-solving, analogy-making and creativity.  Scott is delighted to be in the current position where he can continue and extend upon this work.

Affiliated Researchers

Professor Janet Wiles

Professor Wiles is currently chief investigator in the "Thinking Systems" project within the Division of Complex & Intelligent Systems. Jointly funded by the Australian Research Council (ARC) and the National Health and Medical Research Council (NHMRC), the $3.3 million “Thinking Systems” project brings together specialists in neuroscience, artificial intelligence, robotics and computer science, to study how brains understand spatial systems, both physical and conceptual.  With an extensive background in computational neuroscience, evolutionary computation and machine learning, Janet's expertise and insights are and will be of great benefit to the Fluid Analogies project.
 

Professor Jason Mattingly

An internationally acclaimed neuroscientist,  Professor Mattingly is currently Foundation Chair in Cognitive Neuroscience at The University of Queensland. This is a joint appointment between the Queensland Brain Institute and the School of Psychology, the aim of which is to foster the development of research and teaching links between the disciplines of neuroscience and cognitive science.  As one of the main aims of the Fluid Analogies project is to understand and model the brain mechanisms involved in high-level cognitive functioning, Jason's background in cognitive neuroscience and functional brain imaging techniques is invaluable in the development of such ideas.
 


 
Dr Marcus Gallagher

Dr Gallagher is a senior lecturer in the School of Information Technology and Electrical Engineering at The University of Queensland. His research interests include Metaheuristics and Evolutionary Computation, Machine Learning, Optimization and the Visualization of high-dimensional data.  As a large part of the Fluid Analogies project will involve the implementation of learning (unsupervised, supervised and evolutionary), Marcus' expertise in this area is of great benefit.

Dr Peter Stratton

Dr Stratton is a Research Fellow in the Thinking Systems project, jointly in the Queensland Brain Institute and School of Information Technology and Electrical Engineering at The University of Queensland.  Peter completed his PhD in 2001, developing a novel unsupervised hierarchical learning algorithm for the neocortex.  Affiliation with the Fluid Analogies group will enable Peter to continue this line of research, in the development of self-organising computational architectures based on the neocortex that can learn to perform a wide range of cognitive competencies (such as vision, motor control, prediction and language).

PhD Students

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