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Detecting Key Concepts from Low-Quality Data for Better Decision (2023–2026)

Abstract:
The project aims to develop data analytics techniques that aid better decision making in high-stake scenarios when data are less-trustable. While data-aided decision making has been widely used, less-trustable data may significantly distort the decisions made and hurt people impacted by these decisions. The outcome of this project expects to be a series of techniques covering data understanding and enhancement, model development and fitting, and novelty detection, to reduce the damage of less-trustable data. The research expects to benefit the people and companies impacted by data-aided decision making in cybersecurity, healthcare and financial fraud detection, providing risk-control services.
Grant type:
ARC Discovery Early Career Researcher Award
Researchers:

  • Dr Miao Xu

    ARC DECRA
    School of Electrical Engineering and Computer Science
    Faculty of Engineering, Architecture and Information Technology
    ARC DECRA
    School of Electrical Engineering and Computer Science
    Faculty of Engineering, Architecture and Information Technology
Funded by:
Australian Research Council