Mental imagery has been an active area of research in cognitive psychology for a number of years, but Janice Glasgow is one of the first people to consider imagery as a reasoning paradigm in artificial intelligence. Computational imagery involves the ability to generate, transform, and inspect visual and spatial representations of images to retrieve and reason with information not explicitly stored in long-term memory. For example, a spatial image of a chess board could be reconstructed and then analyzed to determine if a particular motif is a subimage in it.
Glasgow is developing a knowledge representation scheme for imagery. This scheme represents knowledge in terms of a semantic network in long-term memory, organized according to the structural and conceptual hierarchies of the image domain. She has two working-memory representations for visual and spatial reasoning, corresponding to distinct components in human cognition. This research evolved out of her earlier work on programming languages for AI. She was involved in the development of Nial, a high-level programming language based on the mathematics of array theory. The mathematical basis of this language now provides a metalanguage for specifying the representations and primitive functions for computational imagery.
One of the most exciting aspects of this work is an application she and her colleagues are developing with an international team of crystallographers: a knowledge-based approach for molecular reconstruction. The long-term memory model for molecular images is being constructed using crystallographic databases containing over 100,000 previously determined scenes. The researchers are integrating the tools and techniques of computational imagery with aspects of earlier work on Crysalis, recent theoretical advances in protein crystallography and AI, and a more case-based approach to reasoning. This is an ambitious project, with the potential to greatly assist in the determination of protein structures. Currently, a lab may take several years to determine a single structure. Glasgow's group hopes to have a prototype knowledge-based assistant system within a year or two.
Glasgow also believes that imagery is an important alternative reasoning paradigm. According to her recent studies in machine learning and database discovery, this knowledge representation scheme may provide powerful tools for classification based on spatial reasoning.
Glasgow was the program cochair of AI '92 and is now president of the Canadian Society for Computational Studies of Intelligence, one of the oldest national AI societies in the world. She is also a principal investigator in the Intelligent Robotics and Intelligent Systems Federal Center of Excellence and the principal researcher on an AI project for the Canadian Space Agency.
Regarding career development for women, she said, ``I think things have improved in the last 20 years. There is a greater awareness among both men and women...Only in the last few years have I been able to find female scientists at similar career points to me. It has been very supportive to talk to them and share experiences.'' Glasgow believes more women need to hold positions that make a difference-on granting committees, program committees, as senior administrators in academia and industry, on boards of directors.
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