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Charles Rahal

PhD
Associate Professor

Charles is a social science methodologist and applied social data scientist with a background in high-dimensional econometrics, having completed his PhD in 2016. Prior to becoming an Associate Professor in Data Science and Informatics, Charles was a Senior Departmental Research Lecturer at the Leverhulme Centre for Demographic Science, and is an Associate Member of Nuffield College. He also sits on the Steering Group of Reproducible Research Oxford, and is a Co-Investigator at the ESRC Centre for Care. As part of his lecturing, he co-convenes Demographic Analysis, Life Course Research, and the Oxford Partner site of the Summer Institute in Computational Social Sciences. In the past, he's taught modules related to financial econometrics, Python for sociologists and statistical software more generally, and replication in open social science. He has recently given workshops and guest lectures on the themes of 'An Introduction to Machine Learning', 'An Introduction to the Command Line' and `LaTeX in 105 Minutes'. He is always interested in hearing from potential co-authors or prospective graduate students who share his enthusiasm for using Python, R, and LaTeX.

Charles is particularly interested in unique Big Data origination processes -- be they unstructured or otherwise -- and how they contribute to social inequality, mobility and stratification more generally. Other current areas of interest include the machine learning methods, civic technology, spatial and time series econometrics, model uncertainty, and scientometrics.

Specific projects underway at present include:

  • A large scientometric review of the 'Evolution of Science'

  • Interperable ways to directly compare predictive systems (the 'Inter-Model Vigorish')

  • Work on inequalities in life expectancy across the very long run (the 'Legacy of Longevity')

  • A library to incorporate model selection, averaging and influence analysis into robustness pipelines

 

Publications

Friday, 01 September 2017
Tropf, F. et al. (2017) “Hidden heritability due to heterogeneity across seven populations.”, Nature Human Behaviour, 1(10), pp. 757–765.
Charles Rahal
Clarke, P. et al. (no date) “Voting Patterns, Mortality, and Health Inequalities in England”, medRxiv.
Charles Rahal
This is the alt text
Email
charles.rahal@demography.ox.ac.uk
Links
Google Scholar
Website
GitHub

Recent

news
4 Apr 2025

New tool could inform our ability to predict health and other outcomes accurately

news
3 Mar 2025

New framework highlights limits of prediction in computational science

news
7 Nov 2024

The role of non-profit organisations in NHS service provision

Charles Rahal

PhD
Associate Professor
This is the alt text
Email
charles.rahal@demography.ox.ac.uk
Links
Google Scholar
Website
GitHub

Charles is a social science methodologist and applied social data scientist with a background in high-dimensional econometrics, having completed his PhD in 2016. Prior to becoming an Associate Professor in Data Science and Informatics, Charles was a Senior Departmental Research Lecturer at the Leverhulme Centre for Demographic Science, and is an Associate Member of Nuffield College. He also sits on the Steering Group of Reproducible Research Oxford, and is a Co-Investigator at the ESRC Centre for Care. As part of his lecturing, he co-convenes Demographic Analysis, Life Course Research, and the Oxford Partner site of the Summer Institute in Computational Social Sciences. In the past, he's taught modules related to financial econometrics, Python for sociologists and statistical software more generally, and replication in open social science. He has recently given workshops and guest lectures on the themes of 'An Introduction to Machine Learning', 'An Introduction to the Command Line' and `LaTeX in 105 Minutes'. He is always interested in hearing from potential co-authors or prospective graduate students who share his enthusiasm for using Python, R, and LaTeX.

Charles is particularly interested in unique Big Data origination processes -- be they unstructured or otherwise -- and how they contribute to social inequality, mobility and stratification more generally. Other current areas of interest include the machine learning methods, civic technology, spatial and time series econometrics, model uncertainty, and scientometrics.

Specific projects underway at present include:

  • A large scientometric review of the 'Evolution of Science'

  • Interperable ways to directly compare predictive systems (the 'Inter-Model Vigorish')

  • Work on inequalities in life expectancy across the very long run (the 'Legacy of Longevity')

  • A library to incorporate model selection, averaging and influence analysis into robustness pipelines

 

Publications

Friday, 01 September 2017
Tropf, F. et al. (2017) “Hidden heritability due to heterogeneity across seven populations.”, Nature Human Behaviour, 1(10), pp. 757–765.
Charles Rahal
Clarke, P. et al. (no date) “Voting Patterns, Mortality, and Health Inequalities in England”, medRxiv.
Charles Rahal

Recent

news
4 Apr 2025

New tool could inform our ability to predict health and other outcomes accurately

news
3 Mar 2025

New framework highlights limits of prediction in computational science

news
7 Nov 2024

The role of non-profit organisations in NHS service provision

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