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Dr Annette Spooner

Senior Research Associate

PhD in Computer Science (UNSW), BSc (Hons Class 1) in Computer Science (UNSW)

Engineering
Computer Science and Engineering

I obtained a PhD in Computer Science from the University of NSW in 2023. I am currently a Senior Research Associate in the School of Computer Science and Engineering at UNSW, working on multi-modal classification models for high-dimensional multi-class data. My main research interest is in the use of machine learning for medical applications and I have worked in both Alzheimer’s disease and liver cancer research, applying machine learning to the task of knowledge discovery and survival analysis. Prior to undertaking my PhD I was an industry-based software engineer, working in many varied roles, including running my own web development business.

E-mail
a.spooner@unsw.edu.au
Location
K17 412-03
  • Journal articles | 2023
    Spooner A; Mohammadi G; Sachdev PS; Brodaty H; Sowmya A, 2023, 'Ensemble feature selection with data-driven thresholding for Alzheimer's disease biomarker discovery', BMC Bioinformatics, 24, http://dx.doi.org/10.1186/s12859-022-05132-9
    Journal articles | 2020
    Spooner A; Chen E; Sowmya A; Sachdev P; Kochan NA; Trollor J; Brodaty H, 2020, 'A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction', Scientific Reports, 10, pp. 20410, http://dx.doi.org/10.1038/s41598-020-77220-w
  • Preprints | 2022
    Spooner A; Mohammadi G; Sachdev PS; Brodaty H; Sowmya A, 2022, Ensemble feature selection with clustering for analysis of high-dimensional, correlated clinical data in the search for Alzheimer's disease biomarkers, , http://arxiv.org/abs/2207.02380v1
    Preprints | 2022
    Spooner A; Mohammadi G; Sachdev PS; Brodaty H; Sowmya A, 2022, Ensemble feature selection with data-driven thresholding for Alzheimer's disease biomarker discovery, , http://arxiv.org/abs/2207.01822v1
    Preprints | 2022
    Spooner A; Mohammadi G; Sachdev PS; Brodaty H; Sowmya A, 2022, Temporal Pattern Mining for Analysis of Longitudinal Clinical Data: Identifying Risk Factors for Alzheimer's Disease, , http://arxiv.org/abs/2209.04793v1

  • Outstanding HDR Student Award 2021
  • The Norman Foo Memorial Best Research Paper Prize 2020
  • Three Minute Thesis Competition - Winner, School and Faculty Heats, 2021
  • Three Minute Thesis Competition - Winner, School heat, Runner-up, Faculty Heat, 2019