The School of Computer Science and Software Engineering is a new structure within the faculty which brings together the research and teaching efforts of four previous disciplines, namely computer science, computer technology, digital systems and software development. The school covers a wide range of activities at the technical end of the computing spectrum, in particular, the science of computing, the underlying software and hardware of computing systems and software engineering. It operates on both the Clayton and Caulfield campuses, and is the largest academic unit of its type in Australia.
The school seeks to provide courses and student supervision of the highest quality, to undergraduate, postgraduate and professional audiences. It seeks to offer its courses in a variety of ways including on-campus, off-campus and by distance teaching. The school's staff view students as their valued customers, and seek to make courses and student contacts attractive and advanced.
The school contributes in substantial ways to the following courses offered by the faculty:
The school encourages joint research and development with appropriate bodies in government, business, industry, academia and both the national and international communities.
The school seeks research support from all appropriate sources and attempts to broaden the base of such support.
The school strives to enhance the working environment by the provision of ample equipment and expert support personnel. To maintain and improve the working environment, the school also:
The school's researchers and scholars seek to advance the state of the art, knowledge and understanding of the discipline with a strong focus on application and practice; to develop cooperative and synergetic research arrangements and teams with academia, industry and government; and to foster educational and research links, nationally and internationally. In these ways the schoolwill enhance the standing of the university.
The school has an extremely broad range of research activities, ranging from fundamental aspects of computing through to the development of real hardware and software systems.
The work in this area has two aspects: investigation of algorithms suitable for hardware implementation - the algorithms include artificial neural networks, meta-heuristic based optimisation algorithms and fuzzy logic; advanced implementation systems such as full custom VLSI systems, programmable devices as FPGAs and EPLDs.
Specific projects and topics include theory of artificial neural networks, unsupervised learning algorithms, feature map formation, stochastic neural networks, biologically motivated structures; application of ANN in the control of nonlinear dynamic systems, early vision algorithms, image coding and processing; hardware implementation of neural networks; analog, digital and hybrid VLSI systems; theory and implementation of high performance meta-heuristic based optimisation algorithms including the hardware implementation of simulated annealing and tabu search algorithms for solving large combinatorial optimisation problems.
Professor D Abramson, Dr A P Paplinski, Mrs N Bhattacharjee, Dr B Qiu, Mr C M Greif.
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.
Associate Professor I Zukerman, Dr K Korb, Dr A Nicholson, Dr D W Albrecht.
Artificial intelligence and software engineering: deduction of induction results; interactive programming; practical theorem proving.
Dr X Wu.
Software agents and machine learning: integration of rules and objects; intelligent adaption machines; knowledge discovery; specifying and refining intentional agency; specifying multi-agent test beds.
Ms S Ramakrishnan, Professor H Schmidt, Dr X Wu.
Intelligent multimedia: intelligent hypermedia systems; intelligent text retrieval.
Professor H Schmidt, Dr X Wu.
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.
Dr L Allison, Dr T I Dix
Dr D Conway, Mr J McCormack, Dr R Pose, Dr K Marriott.
Object-oriented database technology; object management in object-oriented databases and programming environments; data mining and knowledge discovery in databases; transaction management in OODBMS; OODBMS query languages; data mining and knowledge discovery in databases, schema evolution; schema versioning; deductive database using an SQL filter classification scheme; data mining in large commercial databases; schema and view integration; transaction-driven database design; performance modelling of DBMS; SQL pre-processing and optimisation techniques; active database systems; mobile database systems; formal methods in database research; semantic justification of normal form-based designs; conceptual and meta-modelling; interoperability of conceptual modelling techniques.
Professor B Srinivasan,, Dr N Craske, Dr A Zaslavsky, Mr J Ceddia, Mr R Simpson, Mr R Redpath.
Research in this area in concentrated on aspects of fast packet switching which is at the heart of broadband ISDN studies using ATM (Asynchronous Transfer Mode) techniques.
Current work includes the development of an experimental medium speed (2-20Mb/s) local area ATM network for voice and data, including the switching hardware, the routing and management protocols and software, the adaptation layers to carry other protocols such as TCP/IP, and the interface to other devices and networks; the analysis of the performance of ATM protocols, and the interaction of higher-layer protocols in ATM networks; the handling and performance of compressed video and audio streams over ATM networks; attachment and management of small- and large-scale cellular radio to ATM networks; the security of networks, in particular the implementation and management of encryption systems over inter-networked systems.
Associate Professor J W Breen, Ms V Giesemann, Dr C Tellambura, Dr B Qiu.
The research in this area currently covers three main aspects: digital audio, image and video signal processing; computer/robotic vision; and digital signal processing (DSP) applications.
Digital audio, image and video signal processing includes fast algorithms, coding and compression, coding distortion analysis, adaptive quantisation algorithms, filtering, digital signal quality metrics, finite word length computation effects, and computational complexity analysis.
Computer/robotic vision includes active vision algorithms, pattern recognition, neural fuzzy pattern recognition, and motion tracking algorithms.
DSP applications cover active noise cancellation, on-line image processing for industrial processes, noise cancellation for mobile communications, electrical impedance tomography, geophysical data acquisition and processing, implementation of audio and video codecs for multimedia computing, ATM network communications and information processing/retrieval systems, and advanced digital signal processing systems.
Associate Professor H R Wu, Dr A P Paplinski, Dr B Qiu, Mr C M Greif.
Distributed databases; distributed DBMS commit protocols; multi- and federated database systems; data models for mobile information systems; architectures for mobile distributed computing systems; wireless communications; mobile database management; operating system support for mobile computing; mobile workstation power management and optimisation; transaction management models and algorithms; management of network and mobile computers heterogeneity; data and process migration, replication and recovery; mobile access to Internet services; security in mobile computing systems; user interface management for mobile information systems; protocols for mobile computing systems and networks; resource allocation and management in mobile computing environment; legal/social/economic/health issues of mobile computing; resource sharing issues and distributed computing, security and privacy in distributed DBMS; ISDN communications; data communications; cryptography; interactive voice response systems - dialog design issues; voice processing technologies as an interface to database systems; distributed fax service issues; inter-process communication across computer networks; network and distributed systems simulation, modelling and performance analysis; distributed management interface and desktop management.
Professor B Srinivasan, Dr A Zaslavsky, Mr C Avram, Mr S Giles, Mr P Granville.
Distributed object systems and interfaces: adaptive fault tolerance; object request brokers and traders; interoperability; visualisation.
Object discovery and re-engineering: legacy systems migration to client server, object discovery, object models and for legacy systems
Distributed components software architecture: architecture of real-time distributed systems, distributed control systems, real-time object interface definition languages, object architecture definition languages
Ms Sita Ramakrishnan, Ms C Mingins, Dr A.S.M. Sajeev, Dr. Honghua Dai, Dr A Sajeev and Professor H Schmidt.
Systems software for managing GUIs; generalisation of hypercard interfaces; gestures as commands; separation of abstract objects from graphical views; educational multimedia systems.
Professor L M Goldschlager, Dr D M Conway.
Satellite navigation systems and visual map displays; graphical user interface research for applications and operating systems; interactive multimedia teaching tool with hyper-media navigation strategies.
Mr S Giles, Mr B Sier, Ms R Gedge.
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.
Dr S Ray, Dr P Tischer, Dr R Worley.
Hypothesis formation and testing; machine learning; statistical estimation; clustering; classification; decision trees and graphs; analysis of macro-molecules; confirmation theory; causal discovery.
Professor C S Wallace, Dr L Allison, Dr K Korb, Dr G Farr, Dr J Oliver, Dr D Dowe, Dr H Dai, Dr D W Albrecht.
CASE technology; ISDN-based home office technology; business process re-engineering; computer-assisted person identification.
Dr A Zaslavsky, Mr C Avram, Mr J Ceddia.
Knowledge-based modelling for information acquisition and retrieval; archiving and retrieval of massive data archives; framework models as classifiers in corporate knowledge bases; performance issues in string matching algorithms for text databases; use of SGML-structured documents to generate hypertext retrieval systems; text retrieval and natural language; data compression techniques using neural nets; CD-ROM-based data processing technology; knowledge processing and data generation.
Professor B Srinivasan, Dr A Zaslavsky, Mr J Ceddia, Mr D Foott, Mr J Carpenter.
Logic and constraint programming; incremental constraint solving algorithms; program analysis and optimisation; compilation and applications to biology, engineering and financial modelling.
Professor J N Crossley, Dr K Marriott, Dr D W Albrecht, Dr M Garcia de la Banda.
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.
Formal aspects of software engineering: semantic analysis of object-oriented specification; testing based on formal specifications; requirements capture and conceptualisation; integrating specifications and implementations.
Professor John Hurst, Professor Heinz Schmidt, Dr A Sajeev, Ms S Ramakrishnan
Reuse and re-engineering: object frameworks and restructuring; documentation evolution; object-oriented databases and persistence; class libraries; CASE tools.
Ms C Mingins, Ms S Ramakrishnan, Dr A Sajeev, Professor H Schmidt.
Object-oriented software process and measurements: design and project metrics; object-oriented complexity.
Ms C Mingins, Dr A Sajeev, Professor H Schmidt.
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.
Professor C S Wallace, Dr T I Dix, Associate Professor A J Hurst, Dr R Pose.
Classification and feature selection methods; character recognition; document image analysis; speech recognition; statistical, fuzzy mathematical and neural network techniques.
Dr S Ray.
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.
Prof Heinz Schmidt, Dr L Allison, Dr T I Dix, Associate Professor A J Hurst, Dr D M Conway.
In this area, the emphasis is on knowledge-based robot control. Some of the facets of this research include sensor-fusion - establishing knowledge-based and algorithmic strategies for combining multiple sensor signals so that meaningful trajectory commands can be sent to the controlled robot; application of fuzzy-logic control to industrial processes; application of neural networks to robot control; application of robot vision systems to assembly processes; knowledge-based methods for the determination of feasible assembly sequences.
Dr A P Paplinski, Mr G S Lowe, Dr P J Atkinson.
This area concerns the development of software tools to aid the construction of software for high performance computers. It contains the following projects:
Relative debugging: this ARC funded project concerns the development of debugging software for finding errors in programs after than have been ported to other platforms, including high performance parallel systems.
Professor D Abramson, Ms V Giesemann.
Distgributed systems for parametric modelling: this CRC funded project concerns tools for performing parametric modelling experiments where a model is run across a range of different input scenarios. In order to save time, the computations are distributed across a network of workstations. A beta release of the software is available.
Professor D Abramson
Optimising high performance decision support systems: this ARC funded project concerns the development of high performance optimising decision support systems. The environment is being designed to allow engineers and scientists to use computational models within non-linear optimisation algorithms, with the aim of finding optimal parameter settings for complex design problems. The project is initially targetting systems for examining air quality, and is in collaboration with Griffith university, the Queensland Department of Environment and the Environment Protection Agencies of Victoria and Western Australia.
Professor D Abramson
High-performance object technology: object-oriented concurrency - languages and implementation, applications, reasoning, modelling, tools support.
Dr A Sajeev, Professor H Schmidt.
Dedicated virtual reality display hardware to reduce the load on the host computer.
Dr R Pose.
The major in computer science 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-one 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:
The major in computer technology is a sequence of subjects available to students studying for a Bachelor of Computing at Caulfield; the subjects are also available to students in a range of other courses at Caulfield and on other campuses.
The aims of the major are:
The major in software development is a sequence of subjects available to students studying for a Bachelor of Computing at Caulfield; the subjects are also available to students in a range of other courses at Caulfield and on other campuses.
The aim of the major is to provide undergraduate students in computing and other disciplines with the intellectual tools to enable them to apply state-of-the-art knowledge, skills, methods and techniques to the design, implementation, maintenance and modification of software systems. It will also provide the theoretical understanding for learning and for using new methods in the future, and the attitude which sees the constant updating of knowledge as required professional behaviour.
On completion of the major in software development, students will be able to:
The aim of the Bachelor in Digital Systems is to provide an integrated and practical study of computer hardware and software, with a particular emphasis on `embedded systems', ie processor or microprocessor controlled systems with special-purpose software. It is possible to characterise the course as being a synthesis of elements found in both traditional electronic engineering and computer science courses, but with a particular emphasis on the design and development of digital hardware and related controlling software.
Students completing this course will have knowledge of: