Research in the Department of Computer Science and Information Technology
The Department of Computer Science and Information Technology is recognised nationally and internationally for its research.
The Australian Research Council’s Excellence in Research for Australia ranks our research in artificial intelligence, image processing and information systems as above world standard, and we are ranked in the world’s top 400 universities for computer science.
Department researchers are working closely with industry leaders – including Cisco and Optus – on projects that extend the frontiers of knowledge in artificial intelligence, data science and cybersecurity.
Our research supports La Trobe’s five research themes: Sustainable food and agriculture; Resilient environments and communities; Healthy people, families and communities; Understanding and preventing disease; and Social change and equity.
Our researchers specialise in fundamental and applied research to create innovative technical solutions.
Our research is grouped into six key areas:
Area lead: Professor Wei Xiang
Our team specialises in data mining, machine learning, deep learning, computer intelligence and bioinformatics. We deliver solutions to a range of industries including digital health, bioinformatics, digital forensics and government.
We streamline existing machine learning algorithms to enhance cancer detection and prediction, providing insights on genomic data privacy and security. We work on classification processes for non-coding RNA, which plays a role in biological processes associated with disease. And, we create reliable, real-time analysis for detection and prediction of neurological abnormalities in brain signal data.
Our researchers develop techniques that use conjoint mining of data to enable business, biomedicine and power companies to analyse unstructured content from relational databases. We work with Australian road traffic authorities to automatically capture traffic data, and forecast traffic flows to avoid congestion on road networks.
Our team also develops data mining techniques, such as classification and clustering, to help design face image retrieval systems. And, we work with the Australian Institute of Sport, using deep analysis for action-recognition and multi-person tracking of athletes.
Area lead: Professor Naveen Chilamkurti
Our team is working to prevent, identify and counter threats and vulnerabilities that impact users, systems and networks.
We specialise in privacy and access control, Internet of Things and wireless security, incident response and penetration testing, identity and access management, digital forensics and the prevention of cybercrime.
We use artificial intelligence to detect, block and prevent malware infections. We develop artificial intelligence solutions to reduce the manual handling of cybersecurity incidents.
Our researchers have developed a smart grid testbed to model and predict cyber incidents within critical infrastructure, as well as a forensic capability to investigate incidents. We are also developing advanced access control systems to prevent future data breaches and a secure cloud assurance system.
We work with Data61 on developing techniques to measure cyber resilience at a national level. We also work with others to develop tests to identify and assess cybersecurity talent, with a focus on neurodiverse individuals.
Area lead: Professor Wenny Rahayu
Our team specialises in all aspects of building a data engine including data integration, data fragmentation and utility optimisation, data quality, data privacy and security, and the interconnected systems that support reliable and effective use of data and information.
We work on the whole lifecycle of big data management including sourcing, cleaning and pre-processing, integration from multiple heterogenous sources, managing data streaming, data warehousing and data lake, data access control and privacy preservation, and analytics.
We specialise in mobile, distributed and cloud databases, Internet of Things data ecosystem, spatial data management, semantic knowledge and graph databases.
Our work has been applied in many interdisciplinary domains and industries including smart manufacturing plants, air services flight management systems, patient medical records, business and education systems.
Area lead: Associate Professor Simon Egerton
Our team specialises in applied research, knowledge and technology transfer, and the application of current and new disruptive technologies that fundamentally change the way things are done.
We believe the best applications of disruptive technology are those that are co-created, from the ground up, in collaboration with the primary problem owners who understand the needs around the problem.
We work closely with local government authorities and industry partners through the Australian Smart Communities Association, IoT Alliance Australia and the City of Greater Bendigo.
We established an extensive long-range Internet of Things network, spanning Greater Bendigo and based on the LoRaWAN Internet of Things standard. Our network continues to grow and is enabling new protocol developments and innovative large-scale application case studies in a unique living lab environment.
Our team has also established several open-source robot platforms which are helping us engage with projects in telehealth, healthcare, wellbeing and education. And, we have a rapid prototyping platform to create new Internet of Things, robotic tools and technology designs.
Area lead: Professor Henry Duh
Our team are experts in visualisation, interactive media and education technology including information visualisation, human-computer interaction, virtual and augmented reality, image processing and computer vision.
We specialise in visualisation of complex data, virtual reality interaction, biomedical image and interactive analysis, multi-model user interface design and computer-supported collaborative learning.
We explore creative and innovative ways to help designers and artists use digital technologies for art and work.
We develop and apply advanced machine learning models, including deep learning algorithms, to assist with precision diagnosis of lesions in medical scans. We use computer algorithms to analyse images and health data for enhanced decision support systems.
We use deep learning methods to model and understanding user behaviour across digital medias.
We work on approaches that enhance the automatic arrangement of objects in virtual environments, improve gesture-driven interfaces for mobile interaction and investigate optimal gesture interaction design for older people.
And, we investigate cognitive and behavioural issues such as illusions in virtual environments including place illusion (the user’s feeling that they are in another place) and plausibility illusion (the feeling that events the user is seeing are actually happening).
Area lead: Dr Scott Mann
Our team develops leading practices and technologies for tertiary education in computer science, information technology and cybersecurity.
We have extensive experience in practical educational delivery. We are tackling the challenges of pedagogical design, classroom interaction models and alignment toward end-stage employability. Current projects include exploring the needs of students learning code and developing a web application for students to indicate their understanding of material in real time.
We also deliver a range of outreach activities to secondary school students across Victoria.
Together, our research helps students to become the next generation of technology graduates.
Our staff play a key role in La Trobe's research outputs.
The Cisco-La Trobe Centre for Artificial Intelligence and Internet of Things galvanises a decade-long partnership between Cisco and La Trobe University. The Centre is the first of its kind in Australia to exploit the synergy between state-of-the-art artificial intelligence and Internet of Things technologies. It is creating a new home for innovation and collaboration, enabled by access to world-leading programs, to deliver ideas that will drive Australia’s digital future.
Find out more about the Centre.