Department of Computer Science and Software
Engineering
Shaping a research project and finding supervisor(s)
You can spend the first three weeks (often less) at the start of the honours programme to find a research project interesting enough to motivate you for the entire year.
- Find a research area of interest to you, approach the staff members working in this area, and either take on a project offered by the supervisor(s) or discuss to tailor the projects to suit both yours and the supervisors' research interests.
- Bring your own project proposal, find a potential supervisor by browsing through the following information on staff research interests or approach the honours coordinator for help, finetune your proposal to match interests of both parties.
The research project can be supervised by supervisor(s) outside the department, so long as it has a computational focus, but at least one of your supervisors must be an academic within the department.
CSSE Staff and Research Interests
| Link to homepage | Research Interests | ERO Groups | |
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| Bennamoun, W/Prof Mohammed | control theory, robotics, obstacle avoidance, object recognition, artificial neural networks, signal/image processing and computer vision (particularly 3D) |  |
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| Cardell-Oliver, Assoc/Prof Rachel | data mining, wireless sensor networks; computing education; and formal methods in software engineering |
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| Datta, Professor Amitava | parallel and distributed computing, mobile and wireless computing, bioinformatics, social networks, data mining and software testing | |
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| French, Dr Tim | extensions of modal logics, and their applications to formal methods for software engineering. I wrote my PhD thesis on bisimulation quantifiers for modal logics. This work has applications in the automated reasoning about properties of various systems and programs, and particularly for reasoning about different levels of abstraction. Recently, I have also been interested in many epistemic logics and formal langauges, particularly for reasoning about different levels of agent awareness |
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| Glance, Dr David | Techno-sociology, eHealth, Open Source and various other areas | |
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| Huynh, Dr Du | Computer vision and video analysis; in particular, marker-free human motion capture from video, visual tracking, projective geometry, shape and outlier detection from multiple images or video sequences, 3D reconstruction from images, structured light stripe systems. I am also interested in machine learning and pattern recognition | |
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| Liu, Dr Wei |
Text Mining, Natural Language Processing, Data Mining, Dialogue Management and Multi-Agent Systems My research focuses on knowledge engineering for distributed environments. In particular, semi-automatic ontology learning through analysing large text-corpus analysis using techniques including |
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| MacNish, Assoc/Prof Cara | My research focusses on systems that are able to adapt their response to the data, knowledge or environment in which they are working. My students and I study and develop computational systems that employ learning, optimisation and modelling techniques to improve system performance on complex problems. |  |
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| Mian, Assoc/Prof Ajmal | SMART SURVEILLANCE, 3D FACE RECOGNITION, 3D OBJECT RECOGNITION, 3D MODELING,INTERNET KEY EXCHANGE |  |
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| McDonald, Dr Chris | Chris has recently taught in the areas of computer networking; security & privacy; mobile & wireless computing; software design & implementation; C programming; and operating systems at The University of Western Australia and Dartmouth College. Together with these areas, his research interests include wireless, ad-hoc, & mobile networking; network simulation; and software tools for Computer Science Education. | |
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| Reynolds, Assoc/Prof Mark | Logic, geoscience modelling, Ecological Modelling, Software Engineering, and AI and pattern recognition |
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| Smith, Professor David | David is generally interested in all problems in computational biology, including cellular signal transduction, bone, cartilage, tendon, cell mechanics, physiology of the kidney, problems in developmental biology and others. Furthermore, he is interested in all kinds of geotechnical and geoenvironmental engineering problems, but particularly multiscale models for clay soils. Experience as per published papers listed below. |
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| Wise, Dr Michael | Bioinformatics, Computational Biology, Microbial Informatics | |
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| While, Dr Lyndon | Evolutionary algorithms: Walking Fish Group, Industrial applications of EAs, Multi-objective EAs, Noise in EAs, Game-playing EAs, Pub quiz at CIG'08, Special session on EC for Design at CEC'05. Functional programing implementation: Parallel pattern-matching via source-level transformation, Incremental garbage collection via self-modifying code. |
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Faculty Engineering Remote Operation Critical Mass Groups
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Big Data Processing and MiningBig data from engineering projects and research is transforming our world. The opportunities are vast. So are the challenges, generated by the sheer volume and complexity of this data. Engineering projects linked to remote operations typically generate unstructured data sets of hundreds of gigabytes � a size beyond the capabilities of commonly used software tools. From equipment and safety monitoring, to movement sensors and cameras, to satellites and mobile communications, remote engineering data trails are massive.Our aim is to develop new techniques and systems to manage and make sense of big data. |
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Real Time Optimisation, Scheduling and LogisticsIntelligent automation technologies are critical for remote engineering projects. They route vehicles, control storage, schedule labour and resources, organise maintenance and respond to unforeseen events.Our research develops optimisation, scheduling and control solutions for the mining and offshore extraction sectors and associated operations, such as transport, energy supply and the servicing of remote communities. With a strong focus on real-time optimisation, we devise new ways for work plans and models to be rapidly adapted as needed. In addition to extensive technical expertise, the group has extensive experience in applied engineering, combinatorial mathematics, and in delivering practical reasoning and analytical tools across a range of commercial industrial operations. |
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Structural Mechanics, Geomechanics and ComputationUnderpining the future strength of remote engineering structures: We use computational models to predict mechanical structural behaviour and to integrate information supplied from sensors and monitoring for real-time modelling. |
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Engineering System HealthRemote engineering involves asset intensive industries such as energy, mining, infrastructure and transportation. Projects for these industries often include a myriad of assets diversified by function, geographic location and environmental and cultural context. Integrated system models and asset plans are now vital to unlock a project�s potential and provide insight for global business decision-making.Our researchers aim to bring significant change in the field of asset health management with improved sensing diagnostics and prognostics. We identify and minimise the gaps between research frontiers and practical application to improve predictive asset management, operation fault detection and a project�s overall lifecycle performance. |
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BioengineeringBioengineering integrates knowledge in engineering, medicine and the life sciences. Examples of research areas include: computational and systems biology and computational physiology, biomechanics (computational, soft tissue, prosthesis design and integration with biological systems),biomaterials (tissue properties and engineering, bio-replacement materials), biosensors and systems, biomedical optics, biophotonics, and bioimaging, clinical medicine (medical device engineering, biomedical diagnostics, surgical guidance and simulation, medical imaging and analysis, mathematical medicine, e-health informatics) |
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Robotics and AutomationDeveloping smater autonomous systems: Providing expertise and solutions to spatial awareness and remote autonomous operations of robotic systems. Unmanned and remote autonomous systems and self-directed, maneuverable and interactive robots will allow us to go boldly where no one has gone before. |
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Complex Data ModellingUnderstanding complex systems and engineering data - big or small. Using innovative techniques, we develop mathematical, statistical and computational methodology to support engineering projects. Our research focus is on the challenges of model-building, in the face of engineering data � big or small. We collaborate closely with the Big Data Processing and Mining research group. |
Department of Computer Science and Software Engineering
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CRICOS Code: 00126G
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Last Edited on:Thursday 16th of August 2018 03:48:53 AM
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