Data Science Research

Data Science

Large amount of data are created daily through web query logs, blogs, social media posts and information captured by satellites, sensors or medical devices.

The data science research in CDU focuses on data mining, data management, machine learning, data analysis and information visualisation. The purpose of the research group is to create systems and algorithms to extract useful information, finding correlations and predict trends from large databases for various applications and visualisation. Research areas include:

  • Managing, sorting and extracting useful information from very large amount of data in the field of medical sciences, cyber security, bio-informatics and engineering
  • Managing and integrating different forms of data as they come in various forms such as text, audio, video or images
  • Finding ways to increase the processing speed through enhanced algorithms or integration of high performing computing platforms
  • Designing more useful friendly platforms to improve the communication systems and feedback between the machines, algorithms and people

Parameterized Complexity as a methodology is a specific focus of the research group. It is a recent branch of computational complexity theory that provides a framework for a refined analysis of hard algorithmic problems. The big, important problems facing Planet Earth have structure with “secondary” measurements (parameters), apart from the primary measurement of overall input size, that significantly affect problem computational complexity. The central notion of fixed parameter tractability (FPT) is a generalization of polynomial-time based on confining any non-polynomial (typically exponential) complexity costs to a function only of these secondary measurements. Parameterized algorithms have strong connections to heuristics for NP-hard problems, and the multivariate approach allows more realistic modelling of real-world input distributions. More information  about Parameterizes Complexity research at Charles Darwin University can be found at www.cdu.edu.au/engit/pcru.

Potential areas of PhD and Master by Research topics include:

  • Foundational multivariate algorithmics; including for example, research into interconnections with heuristics and approximations.
  • Applications in analysing massive data sets, bioinformatics and biomedicine, artificial intelligence, computational social choice, cognitive science, ecology, and other disciplines.

Research Coordinator: Charles Yeo

ENGINEERING & IT