Dr Meagan Carney
Dr

Meagan Carney

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Availability

Dr Meagan Carney is:
Available for supervision
Media expert

Qualifications

  • Doctor of Philosophy, Institution to be confirmed

Research interests

  • Extreme Value Theory

  • Chaotic Dynamical Systems

  • Extreme Weather Events

  • Rare Event Analysis

  • Machine Learning

Search Professor Meagan Carney’s works on UQ eSpace

21 works between 2017 and 2026
All (21) Journal Article (15) Other Outputs (5) Conference Publication (1)

21 - 21 of 21 works

2017

Journal Article

Dynamical Borel-Cantelli lemmas and rates of growth of Birkhoff sums of non-integrable observables on chaotic dynamical systems

Carney, Meagan and Nicol, M. (2017). Dynamical Borel-Cantelli lemmas and rates of growth of Birkhoff sums of non-integrable observables on chaotic dynamical systems. Nonlinearity, 30 (7), 2854-2870. doi: 10.1088/1361-6544/aa72c2

Dynamical Borel-Cantelli lemmas and rates of growth of Birkhoff sums of non-integrable observables on chaotic dynamical systems

Current funding

  • 2026 - 2029
    Mathematics of Extremes in Random Dynamics for Catastrophic Event Risk (UNSW administered ARC Discovery Project)
    University of New South Wales
    Open grant
  • 2024 - 2027
    Glycaemic variability: A culprit cause of heart disease in diabetes
    MRFF Targeted Translation Research Accelerator
    Open grant
  • 2024 - 2026
    ALL IN - AI and Laboratory Led IdentificatioN of PASC
    NHMRC MRFF Post-Acute Sequelae of COVID-19
    Open grant

Availability

Dr Meagan Carney is:
Available for supervision

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Available projects

  • Statistical Modelling of Extreme Weather Events in a Changing Climate

    Extremes in weather, such as tropical storms, wildfires, heatwaves, or large-scale floods can have massive societal and economic impacts from loss of property to loss of life. In this project, we seek answers to return times and magnitudes of extreme weather events in a region. We use a combination of extreme value theory, numerical global circulation models, classification algorithms, and real-world data to mathematically map out weather regions and form regional models of weather extremes. We also consider changes in the probabilities of these events under standard climate cycles and increased CO2 emission thresholds.

  • Rare Event Analysis and Machine Learning Applications to SARS-CoV-2

    This project has many available branches for exploration, utilising both unsupervised and supervised machine learning methods. We combine virology experimental data with cutting-edge statistical methods to answer questions ranging from early detection of SARS-CoV-2 infection to mutation paths and likelihoods.

Supervision history

Current supervision

Completed supervision

Enquiries

Contact Dr Meagan Carney directly for media enquiries about:

  • extremes
  • machine learning
  • rare events

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