The department is dedicated (a) to research that advances the growth of knowledge and understanding of the science of computing; (b) to educating undergraduates and postgraduates to their full potential; (c) to developing links with government, business, industry, academia and the community; and (d) to providing an intellectual and physical environment in which all its staff and students can perform to the best of their ability.
The department provides a broad range of courses to cater for the wide variety of students interested in computing. In its teaching, the department:
The department carries out basic and strategic research in computing hardware, software and theory, building on its strengths which currently include inference, image processing and graphics, artificial intelligence and computer systems.
It maintains and develops its individual and group links with the international computer science community, publishing and presenting its results in artefacts, software and papers at conferences and in journals, both international and local.
The department aims to provide an environment in which all its members, staff and students alike, can carry out their research. It encourages cooperation and the effective and efficient use of resources.
It actively recruits the highest quality staff and research students.
The department encourages joint research and development with appropriate bodies in government, business, industry, academia and both the national and international communities.
The department seeks research support from all appropriate sources and attempts to broaden the base of such support.
The department strives to enhance the working environment by the provision of adequate equipment and support personnel. To maintain and improve the working environment, the department also:
For information contact Associate Professor A J Hurst, telephone (03) 9905 5192.
Inductive inference
Hypothesis formation and testing; machine learning; statistical estimation; clustering; classification; decision trees and graphs; analysis of macro-molecules; confirmation theory; causal discovery.
Lossless image compression, greyscale and colour; segmentation and classification of greyscale and colour images; 3D reconstruction of laser confocal microscopy images; colour space; texture characterisation; image restoration.
Shared-memory and distributed shared-memory multiprocessor computer systems; techniques for managing the distribution of data and control over large scale massively-parallel computer systems from both the functional viewpoint and in terms of the practicalities of implementation; prototype hardware implementations; system clocking, data routing, data buffering, memory allocation, caching techniques and communication technology.
Capability-based persistent operating systems and languages; the mapping of capability systems onto various architectures in a reasonably portable manner; the implementation of shared libraries; optimal times for binding of objects; user interface; compatibility with conventional systems and multilingual support; persistent object reuse issues; computer system specification; computer system support for software engineering.
Dedicated virtual reality display hardware to reduce the load on the host computer.
Logic and constraint programming; incremental constraint solving algorithms; program analysis and optimisation; compilation and applications to biology, engineering and financial modelling.
Agent modelling; discourse planning; multimedia interfaces; speech recognition; machine learning; knowledge representation; cognitive science; philosophy of artificial intelligence; philosophy of cognition and consciousness; planning; reasoning under uncertainty; evolutionary algorithms; argument analysis and generation.
Systems software for managing GUIs; generalisation of hypercard interfaces; gestures as commands; separation of abstract objects from graphical views; educational multimedia systems.
Stochastic algorithms for map assembly using restriction, finger-print and other data; exhaustive and stochastic algorithms for DNA string comparison and overlap assembly; generic interface and database development for capturing experimental data from the Human Genome project and for subsequent analysis.
Development of parallel programming systems; introduction of safety into existing languages; functional programming; object-oriented programming; formal specification; human factors in the design of teaching languages; literate programming; parallel programming.
Classification and feature selection methods; character recognition; document image analysis; speech recognition; statistical, fuzzy mathematical and neural network techniques.
The major in computer science is the principal undergraduate offering of the Department of Computer Science. The major is a sequence of subjects available to students studying for a Bachelor of Computer Science; the major is also available to students in a range of other courses, including the Bachelor of Science and Bachelor of Computer Science and Engineering.
Students completing a major in computer science are eligible for level 1 membership of the Australian Computer Society.
The aim of the major is to provide students with both practical skills and a conceptual understanding of computer science, focusing on four main areas of study: algorithms, computing machinery, theory, and applications. Teaching is directed at giving students not only the essential facts in these areas, but also an understanding of the concepts and principles that underlie and interrelate them.
Students completing this sequence will have knowledge and understanding of the following areas:
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