Overview
Research Interests
- Extreme Value Theory
- Chaotic Dynamical Systems
- Extreme Weather Events
- Rare Event Analysis
- Machine Learning
Qualifications
- Doctor of Philosophy
Publications
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Journal Article: Hurricane simulation and nonstationary extremal analysis for a changing climate
Carney, Meagan, Kantz, Holger and Nicol, Matthew (2022). Hurricane simulation and nonstationary extremal analysis for a changing climate. Journal of Applied Meteorology and Climatology, 61 (11), 1629-1642. doi: 10.1175/JAMC-D-22-0003.1
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Journal Article: Extremes and extremal indices for level set observables on hyperbolic systems
Carney, Meagan, Holland, Mark and Nicol, Matthew (2021). Extremes and extremal indices for level set observables on hyperbolic systems. Nonlinearity, 34 (2), 1136-1167. doi: 10.1088/1361-6544/abd85f
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Journal Article: Robust regional clustering and modeling of nonstationary summer temperature extremes across Germany
Carney, Meagan and Kantz, Holger (2020). Robust regional clustering and modeling of nonstationary summer temperature extremes across Germany. Advances in Statistical Climatology, Meteorology and Oceanography, 6 (1) ascmo-6-61-2020, 61-77. doi: 10.5194/ascmo-6-61-2020
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Journal Article: Nonstationarity of summer temperature extremes in Texas
Carney, Meagan, Azencott, Robert and Nicol, Matthew (2020). Nonstationarity of summer temperature extremes in Texas. International Journal of Climatology, 40 (1), 620-640. doi: 10.1002/joc.6212
Supervision
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Statistical Models of Extreme Weather Events in a Changing Climate
Doctor Philosophy
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Global stability of chaotic random dynamical systems
Doctor Philosophy
-
Random Dynamical Systems, Transfer Operators and Stability
Doctor Philosophy
Available Projects
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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.
Publications
Featured Publications
-
Hurricane simulation and nonstationary extremal analysis for a changing climate
Carney, Meagan, Kantz, Holger and Nicol, Matthew (2022). Hurricane simulation and nonstationary extremal analysis for a changing climate. Journal of Applied Meteorology and Climatology, 61 (11), 1629-1642. doi: 10.1175/JAMC-D-22-0003.1
-
Extremes and extremal indices for level set observables on hyperbolic systems
Carney, Meagan, Holland, Mark and Nicol, Matthew (2021). Extremes and extremal indices for level set observables on hyperbolic systems. Nonlinearity, 34 (2), 1136-1167. doi: 10.1088/1361-6544/abd85f
-
Robust regional clustering and modeling of nonstationary summer temperature extremes across Germany
Carney, Meagan and Kantz, Holger (2020). Robust regional clustering and modeling of nonstationary summer temperature extremes across Germany. Advances in Statistical Climatology, Meteorology and Oceanography, 6 (1) ascmo-6-61-2020, 61-77. doi: 10.5194/ascmo-6-61-2020
-
Nonstationarity of summer temperature extremes in Texas
Carney, Meagan, Azencott, Robert and Nicol, Matthew (2020). Nonstationarity of summer temperature extremes in Texas. International Journal of Climatology, 40 (1), 620-640. doi: 10.1002/joc.6212
Journal Article
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Runs of extremes of observables on dynamical systems and applications
Carney, Meagan, Holland, Mark, Nicol, Matthew and Tran, Phuong (2024). Runs of extremes of observables on dynamical systems and applications. Physica D: Nonlinear Phenomena, 460 134093, 134093. doi: 10.1016/j.physd.2024.134093
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Carney, Meagan, Pelaia, Tiana Maria, Chew, Tracy, Teoh, Sally, Phu, Amy, Kim, Karan, Wang, Ya, Iredell, Jonathan, Zerbib, Yoann, McLean, Anthony, Schughart, Klaus, Tang, Benjamin, Shojaei, Maryam, Short, Kirsty R and PREDICT-19 consortium (2024). Host transcriptomics and machine learning for secondary bacterial infections in patients with COVID-19: a prospective, observational cohort study. The Lancet Microbe, 5 (3), e272-e281. doi: 10.1016/S2666-5247(23)00363-4
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Blood transcriptome responses in patients correlate with severity of COVID-19 disease
Wang, Ya, Schughart, Klaus, Pelaia, Tiana Maria, Chew, Tracy, Kim, Karan, Karvunidis, Thomas, Knippenberg, Ben, Teoh, Sally, Phu, Amy L., Short, Kirsty R., Iredell, Jonathan, Thevarajan, Irani, Audsley, Jennifer, Macdonald, Stephen, Burcham, Jonathon, McLean, Anthony, Tang, Benjamin, Shojaei, Maryam, PREDICT-19 consortium, Kulasinghe, Arutha and Carney, Meagan E. (2023). Blood transcriptome responses in patients correlate with severity of COVID-19 disease. Frontiers in Immunology, 13 1043219, 1-18. doi: 10.3389/fimmu.2022.1043219
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Elevated BMI reduces the humoral response to SARS‐CoV‐2 infection
Tong, Marcus ZW, Sng, Julian DJ, Carney, Meagan, Cooper, Lucy, Brown, Samuel, Lineburg, Katie E, Chew, Keng Yih, Collins, Neve, Ignacio, Kirsten, Airey, Megan, Burr, Lucy, Joyce, Briony A, Jayasinghe, Dhilshan, McMillan, Christopher LD, Muller, David A, Adhikari, Anurag, Gallo, Linda A, Dorey, Emily S, Barrett, Helen L, Gras, Stephanie, Smith, Corey, Good‐Jacobson, Kim and Short, Kirsty R (2023). Elevated BMI reduces the humoral response to SARS‐CoV‐2 infection. Clinical & Translational Immunology, 12 (12) e1476, e1476. doi: 10.1002/cti2.1476
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Hurricane simulation and nonstationary extremal analysis for a changing climate
Carney, Meagan, Kantz, Holger and Nicol, Matthew (2022). Hurricane simulation and nonstationary extremal analysis for a changing climate. Journal of Applied Meteorology and Climatology, 61 (11), 1629-1642. doi: 10.1175/JAMC-D-22-0003.1
-
Extremes and extremal indices for level set observables on hyperbolic systems
Carney, Meagan, Holland, Mark and Nicol, Matthew (2021). Extremes and extremal indices for level set observables on hyperbolic systems. Nonlinearity, 34 (2), 1136-1167. doi: 10.1088/1361-6544/abd85f
-
Robust regional clustering and modeling of nonstationary summer temperature extremes across Germany
Carney, Meagan and Kantz, Holger (2020). Robust regional clustering and modeling of nonstationary summer temperature extremes across Germany. Advances in Statistical Climatology, Meteorology and Oceanography, 6 (1) ascmo-6-61-2020, 61-77. doi: 10.5194/ascmo-6-61-2020
-
Nonstationarity of summer temperature extremes in Texas
Carney, Meagan, Azencott, Robert and Nicol, Matthew (2020). Nonstationarity of summer temperature extremes in Texas. International Journal of Climatology, 40 (1), 620-640. doi: 10.1002/joc.6212
-
Compound Poisson Law for Hitting Times to Periodic Orbits in Two-Dimensional Hyperbolic Systems
Carney, Meagan, Nicol, Matthew and Zhang, Hong-Kun (2017). Compound Poisson Law for Hitting Times to Periodic Orbits in Two-Dimensional Hyperbolic Systems. Journal of Statistical Physics, 169 (4), 804-823. doi: 10.1007/s10955-017-1893-9
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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
Conference Publication
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Analysis and simulation of extremes and rare events in complex systems
Carney, Meagan, Kantz, Holger and Nicol, Matthew (2020). Analysis and simulation of extremes and rare events in complex systems. Advances in Dynamics, Optimization and Computation SON 2020, Paderborn, Germany, 28 September - 2 October 2020. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-51264-4_7
PhD and MPhil Supervision
Current Supervision
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Statistical Models of Extreme Weather Events in a Changing Climate
Doctor Philosophy — Principal Advisor
Other advisors:
-
Global stability of chaotic random dynamical systems
Doctor Philosophy — Associate Advisor
Other advisors:
-
Random Dynamical Systems, Transfer Operators and Stability
Doctor Philosophy — Associate Advisor
Other advisors:
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Improved diagnostics for respiratory viral infections
Doctor Philosophy — Associate Advisor
Other advisors:
Possible Research Projects
Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.
-
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.
