Data Mining

Research Area Deputy Leader

Ashad Kabir

Dr Ashad Kabir

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
Abeer Alsadoon Abeer Alsadoon Adjunct Associate Professor Study Centre Sydney

Irfan Atlas

Irfan Altas Associate Professor Wagga Wagga

Xiaodi Huang

Xiaodi Huang Associate Professor Albury 

Ryan Ip

Ryan Ip Lecturer Wagga Wagga 

Rafiqul Islam

Rafiqul Islam Associate Professor Albury

Zahid Islam

Zahid Islam Professor Bathurst

Ashad Kabir

Ashad Kabir Senior Lecturer Bathurst 

Chang-Tsun Li

Chang-Tsun Li Professor   

Xufeng Lin

Xufeng Lin Adjunct Associate Lecturer Wagga Wagga 

Quazi Mamun

Quazi Mamun Senior Lecturer Wagga Wagga 

Azizur Rahman

Azizur Rahman Associate Professor Wagga Wagga  

Sabih Rehman

Sabih Rehman Senior Lecturer Wagga Wagga 

David Tien

David Tien Senior Lecturer Bathurst 

Lihong Zhen

Lihong Zheng Associate Professor Wagga Wagga

Funded Projects:

  • Prof. Zahid Islam and Prof. Mark MorrisonProvision of a Predictive Risk Stratification Tool for the Chronic/Complex Healthcare: Engaging Stakeholders and Services (CHESS) Initiative.
    Funded by Murrumbidgee Local Health District (MLHD), NSW Health $52,677.
  • Prof. Oliver Burmeister (Lead CI), Prof. Mark Morrison, Prof. Zahid Islam, A/Prof. Maree Bernoth, and A/Prof. Rylee Dionigi: Social and community links - a driver of healthy and active ageing.
    Department of Social Services, Australia. Partner organisation: Carewest Pty Ltd, Orange, NSW. $655,000 ($60,000 to CSU).
  • Prof. Oliver Burmeister, Prof. Zahid Islam, A/Prof. Maree Bernoth and Ms Carli KulmarSynergy ecosystem data storage: medico-legal and ethical challenges.
    Young and Well Cooperative Research Centre, Australia $16,500.
  • Prof. Mark Morrison, A/Prof. Maree Bernoth, Prof. Oliver Burmeister, and Prof. Zahid Islam: Review of Support Worker Integration with Functional Decline.
    Hobart District Nursing $39,400.
  • Prof. Mark Morrison, Prof. Oliver Burmeister, Prof. Zahid Islam, A/Prof. Ramudu Bhanugopan and A/Prof. Maree Bernoth: Age Care Workforce Reform - Building Communities of Practice Around the Prevention of Functional Decline in the Community.
    Carewest, Australia. $25,000


  • Dr Md Anisur Rahman: Automatic Selection of High Quality Initial Seeds for Generating High Quality Clusters without Requiring any User Inputs.
    Supervisors: A/Prof. Zahid Islam, Prof. Terry Bossomaier, A/Prof. Tanveer Zia
  • Dr Md Geaur Rahman: Data Cleansing for Data Quality Improvement in Data Mining
    Supervisors: A/Prof. Zahid Islam, Prof. Terry Bossomaier.
  • Samuel Fletcher: Data Mining and Privacy: Modeling Sensitive Data with Differential Privacy
    Supervisors: A/Prof. Zahid Islam, A/Prof. Oliver Burmeister
  • Md Nasim Adnan: Decision Tree and Decision Forest Algorithms: On Improving Accuracy, Efficiency and Knowledge Discovery
    Supervisors: A/Prof. Zahid Islam, Dr Md Rafiqul Islam
  • Abul Hashem Beg: A Novel Genetic Algorithm based Clustering and Tree based validation in Producing and Evaluating Sensible Clusters
    Supervisors: A/Prof. Zahid Islam, Prof. Vladimir Estivill-Castro
  • Michael Siers: Software Defect Prediction by Novel Data Mining Algorithms Addressing Class Imbalance and Cost Sensitivity Issues
    Supervisors: A/Prof. Zahid Islam, Prof. Terry Bossomaier
  • Mohammad Khubeb Siddiqui: Brain Data Mining for Disease Detection and Prediction
    Supervisors: A/Prof. Zahid Islam, Dr Ashad Kabir
  • Khondker Jahid Reza: Novel Techniques to Protect Privacy of Online Social Media Users from Malicious Data Miners
    Supervisors: A/Prof. Zahid Islam, Prof. Vladimir Estivill-Castro, Prof. Terry Bossomaier
  • Darren Bradley Yates: 3D Data Mining and Visualisation
    Supervisors: A/Prof. Zahid Islam, Prof Junbin Gao
  • Nectarios Costadopoulos: Data Mining for Emotion Detection through Wearable Devices
    Supervisors: A/Prof. Zahid Islam, Prof. Terry Bossomaier

Visitors in 2016

A group of three academics from China and Queensland visited us on 18 October, 2016. The members of the research area met the visitors and discussed collaboration opportunities. The visitors were as follows:

  • A/Prof. Ji Zhang, Department of Mathematics and Computing, the University of Southern Queensland (USQ), Australia.
  • Professor Yonglong Luo, Vice-Dean, School of Mathematics & Computer Science, Anhui Normal University, China.
  • Professor Fulong Chen, Deputy Director, Department of Computer Science and Technology, School of Mathematics and Computer Science, Anhui Normal University, China.

Group Activities

Monthly lunchtime meetings, where:

  • Members will inform about their recent research activities,
  • A member will give a short 10 minutes talk on a recent paper followed by a discussion,
  • Research collaboration ideas and necessary resources will be discussed,
  • An external guest will be invited when possible to explore collaboration with him/her, and
  • Mentors/Senior Researchers will be invited when possible.

Research Retreats, where:

  • Members will spend time in brainstorming,
  • Senior Researchers will be invited to give seminars and discuss collaboration opportunities, and
  • Industry Colleagues will be invited to facilitate discussions on real life problems and collaboration.