Welcome to the Data Mining Research Group page in DSRU at Charles Sturt.

We partner with industry to find solutions to current and future challenges in the 21st Century’s data centric world. Data mining techniques and applied statistics approaches are at the core of data science. Data mining is also known as data analytics, knowledge discovery, machine learning and predictive modelling. Huge amount of data are being collected in every sector of life today, making data mining an extremely important area of research. It is useful for data collection, data pre-processing and cleansing, knowledge discovery, event detection, future prediction, policy analysis, strategy development, and real-life applications of (big) data-driven reasoning.

This multidisciplinary group consists of nationally and internationally recognised researchers who are expert in developing novel techniques, models and algorithms for all aspects of data mining. The research group is actively collaborating with professional practitioners from business organisations, academia, and regional and wider authorities. We conduct research that focus on a range of key themes including population health, big and complex data analysis, agricultural modelling, sustainable environment and farming, cyber security, social network data mining, and applied statistics and policy analysis for example.

The data mining research group has a modern Data Analytics Lab with leading-edge equipment and data analysis tools. This lab has high performance Lambda Blade computing facilities, iPhone with 3D camera, Raspberry Pi 3, Plus 8 Touch 4, Drone, Arduino Uno R3, Empatica E4, small robots and conferencing facility. Further detailed information of our lab will be available HERE (soon).

The primary objective of the research group is to coordinate activities and facilitate open scholarly research and learning opportunities so that together we can be insightful and inclusive, as well as achieve impactful and inspiring outcomes around our Charles Sturt ethos. Some specific objectives follow.

• Arouse research participation and students’ learning through proactive collaboration, trustful partnership and safe research environment.
• Bestow services to our communities both jointly and individually through research engagement, innovation and addressing contemporary social issues.
• Create opportunities for people and organisations who need our support through high quality research training and effective research outcomes.
• Develop significant knowledge and nurture mutual benefit for our partners through data mining research.

If you would like to join this research group or would like more information please contact the Research Area Leader.

Our research is funded by various organisations including:

• ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS)
• Australian Capital Territory – Land Development Agency
• Australian Commonwealth Department of Health and Aging
• Australian Government Department of Education, Skills and Employment
• Australian Government Department of Infrastructure, Transport, Regional Development and Communications
• Carewest
• Cyber Security CRC
• Department of Social Services
• Food Agility CRC
• Hobart District Nursing
• Institute for Governance and Policy Analysis
• National Centre for Social and Economic Modelling and The Treasury
• NSW Department of Primary Industries (DPI)
• NSW Health
• Statistical Society of Australia
• Young and Well Cooperative Research Centre