Faculty/School

Faculty of Science

School of Mathematical Sciences

Topic status

We're looking for students to study this topic.

Research centre

Centre for Data Science

Primary Supervisor

Associate Professor Gentry White
Position
Associate Professor
Division / Faculty
Faculty of Science

Other QUT supervisors

Professor Helen Thompson
Position
Professor
Division / Faculty
Faculty of Science

External supervisors

  • Summer Wang, Australian Bureau of Statistics
  • Lyndon Ang, Australian Bureau of Statistics

Overview

Outliers are anomalous observations in a data set that are "outside the norm" of what would be expected. Identifying outliers is an important part of exploratory data analysis and data analysis in general. It is often a challenging problem and calls for advanced methods and approaches, including machine learning-based tools. As methods become more and more complex, their explainability becomes more difficult and more important. This research project will look at all aspects of explainability and explore new approaches and methods.

Research engagement

Critical Literature Review, Computational Implementation and Evaluation

Research activities

Research activities could include, but are not limited to, discussing and recommending explainability methods for outlier detection.  Testing can be done on publicly accessible datasets that are commonly used in outlier detection research.

Research skills

Critical Thinkin, Software  Literarcy, Written Communication

Skills and experience

A data-science, mathematics, or computer science background is recommended.

Start date

2 November, 2026

End date

19 February, 2027

Location

GP Y Block Level 8

Keywords

Contact

Gentry White

3138 1658

whiteg5@qut.edu.au