Skip to main content
Oxford uni Logo
LCDS Logo

  • Home
  • About
    • The Centre
    • Our Partners
    • Work with us
    • Contact us
    • Governance
  • People
  • Research
    • Publications
    • Research areas
    • Data dashboards
  • News
    • News Articles
    • In the Media
Search
  • Home
  • About
    • The Centre
    • Our Partners
    • Work with us
    • Contact us
    • Governance
  • People
  • Research
    • Publications
    • Research areas
    • Data dashboards
  • News
    • News Articles
    • In the Media

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

Tuesday, 04 March 2025
Yan, J. and Rahal, C. (2025) “On the unknowable limits to prediction”, Nature Computational Science [Preprint].
Charles Rahal
Friday, 07 February 2025
Muggleton, N., Rahal, C. and Reeves, A. (2025) “Capitalizing on a crisis: a computational analysis of all five million British firms during the Covid-19 pandemic”, Journal of Computational Social Science, 8(2).
Charles Rahal
Wednesday, 04 September 2024
Rahal, C. and Mohan, J. (2024) “The role of the third sector in public health service provision: evidence from 25,338 heterogeneous procurement datasets”, Journal of the Royal Statistical Society Series A: Statistics in Society [Preprint].
Charles Rahal
Monday, 03 June 2024
Domingue, B. et al. (2024) “The intermodel vigorish as a lens for understanding (and quantifying) the value of item response models for dichotomously coded items”, Psychometrika [Preprint].
Charles Rahal
Monday, 01 April 2024
Rahal, C., Verhagen, M. and Kirk, D. (2024) “The rise of machine learning in the academic social sciences”, AI & SOCIETY, 39(2), pp. 799–801.
Charles Rahal
Monday, 26 February 2024
Newman, S. et al. (2024) “Publisher Correction: Offshoring emissions through used vehicle exports”, Nature Climate Change, 14(3), pp. 297–297.
Charles Rahal
Wednesday, 21 February 2024
Newman, S. et al. (2024) “Offshoring Emissions through Used Vehicle Exports”, arXiv.
Charles Rahal
Tuesday, 20 February 2024
Newman, S. et al. (2024) “Offshoring emissions through used vehicle exports”, Nature Climate Change, 14(3), pp. 238–241.
Charles Rahal
Tuesday, 23 August 2022
Rahal, C., Verhagen, M. and Kirk, D. (2022) “The rise of machine learning in the academic social sciences”, AI and Society, 39(2), pp. 799–801.
Charles Rahal
Monday, 13 December 2021
Mills, M. and Rahal, R. (2021) “Population studies at 75 years: an empirical review”, Population Studies, 75(S1), pp. 7–25.
Charles Rahal
Wednesday, 20 October 2021
Goodair, B., Reeves, A. and Rahal, C. (2021) “Is outsourcing healthcare to private providers associated with higher mortality rates in NHS England?”, European Journal of Public Health, 31(Supplement_3), p. ckab164.836.
Charles Rahal
Sunday, 26 September 2021
Aburto, J. et al. (2021) “Quantifying impacts of the COVID-19 pandemic through life expectancy losses: a population-level study of 29 countries”, International Journal of Epidemiology, 51(1), pp. 63–74.
Charles Rahal
Sunday, 26 September 2021
Aburto, J. et al. (2021) “Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries.”, International journal of epidemiology [Preprint].
Charles Rahal
Thursday, 04 June 2020
Block, P. et al. (2020) “Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world”, Nature Human Behaviour, 4, pp. 588–596.
Charles Rahal
Wednesday, 15 April 2020
Block, P. et al. (2020) “Social network-based distancing strategies to flatten the COVID 19 curve in a post-lockdown world”, arXiv.
Charles Rahal
Thursday, 05 March 2020
Mills, M. and Rahal, C. (2020) “The GWAS Diversity Monitor tracks diversity by disease in real time”, Nature Genetics, 52(3), pp. 242–243.
Charles Rahal
Wednesday, 10 July 2019
Rahal, R. (2019) “Tools for transparency in central government spending”, International Journal of Population Data Science, 4(1).
Charles Rahal
Monday, 07 January 2019
Mills, M. and Rahal, C. (2019) “A scientometric review of genome-wide association studies”, Communications Biology, 2.
Charles Rahal
Friday, 20 April 2018
Rahal, C. (2018) “The keys to unlocking public payments data”, Kyklos, 71(2), pp. 310–337.
Charles Rahal
Sunday, 29 October 2017
Reeves, A. et al. (2017) “The decline and persistence of the old boy: Private schools and elite recruitment 1897 to 2016”, American Sociological Review, 82(6), pp. 1139–1166.
Charles Rahal
  • Load More
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

Tuesday, 04 March 2025
Yan, J. and Rahal, C. (2025) “On the unknowable limits to prediction”, Nature Computational Science [Preprint].
Charles Rahal
Friday, 07 February 2025
Muggleton, N., Rahal, C. and Reeves, A. (2025) “Capitalizing on a crisis: a computational analysis of all five million British firms during the Covid-19 pandemic”, Journal of Computational Social Science, 8(2).
Charles Rahal
Wednesday, 04 September 2024
Rahal, C. and Mohan, J. (2024) “The role of the third sector in public health service provision: evidence from 25,338 heterogeneous procurement datasets”, Journal of the Royal Statistical Society Series A: Statistics in Society [Preprint].
Charles Rahal
Monday, 03 June 2024
Domingue, B. et al. (2024) “The intermodel vigorish as a lens for understanding (and quantifying) the value of item response models for dichotomously coded items”, Psychometrika [Preprint].
Charles Rahal
Monday, 01 April 2024
Rahal, C., Verhagen, M. and Kirk, D. (2024) “The rise of machine learning in the academic social sciences”, AI & SOCIETY, 39(2), pp. 799–801.
Charles Rahal
Monday, 26 February 2024
Newman, S. et al. (2024) “Publisher Correction: Offshoring emissions through used vehicle exports”, Nature Climate Change, 14(3), pp. 297–297.
Charles Rahal
Wednesday, 21 February 2024
Newman, S. et al. (2024) “Offshoring Emissions through Used Vehicle Exports”, arXiv.
Charles Rahal
Tuesday, 20 February 2024
Newman, S. et al. (2024) “Offshoring emissions through used vehicle exports”, Nature Climate Change, 14(3), pp. 238–241.
Charles Rahal
Tuesday, 23 August 2022
Rahal, C., Verhagen, M. and Kirk, D. (2022) “The rise of machine learning in the academic social sciences”, AI and Society, 39(2), pp. 799–801.
Charles Rahal
Monday, 13 December 2021
Mills, M. and Rahal, R. (2021) “Population studies at 75 years: an empirical review”, Population Studies, 75(S1), pp. 7–25.
Charles Rahal
Wednesday, 20 October 2021
Goodair, B., Reeves, A. and Rahal, C. (2021) “Is outsourcing healthcare to private providers associated with higher mortality rates in NHS England?”, European Journal of Public Health, 31(Supplement_3), p. ckab164.836.
Charles Rahal
Sunday, 26 September 2021
Aburto, J. et al. (2021) “Quantifying impacts of the COVID-19 pandemic through life expectancy losses: a population-level study of 29 countries”, International Journal of Epidemiology, 51(1), pp. 63–74.
Charles Rahal
Sunday, 26 September 2021
Aburto, J. et al. (2021) “Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries.”, International journal of epidemiology [Preprint].
Charles Rahal
Thursday, 04 June 2020
Block, P. et al. (2020) “Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world”, Nature Human Behaviour, 4, pp. 588–596.
Charles Rahal
Wednesday, 15 April 2020
Block, P. et al. (2020) “Social network-based distancing strategies to flatten the COVID 19 curve in a post-lockdown world”, arXiv.
Charles Rahal
Thursday, 05 March 2020
Mills, M. and Rahal, C. (2020) “The GWAS Diversity Monitor tracks diversity by disease in real time”, Nature Genetics, 52(3), pp. 242–243.
Charles Rahal
Wednesday, 10 July 2019
Rahal, R. (2019) “Tools for transparency in central government spending”, International Journal of Population Data Science, 4(1).
Charles Rahal
Monday, 07 January 2019
Mills, M. and Rahal, C. (2019) “A scientometric review of genome-wide association studies”, Communications Biology, 2.
Charles Rahal
Friday, 20 April 2018
Rahal, C. (2018) “The keys to unlocking public payments data”, Kyklos, 71(2), pp. 310–337.
Charles Rahal
Sunday, 29 October 2017
Reeves, A. et al. (2017) “The decline and persistence of the old boy: Private schools and elite recruitment 1897 to 2016”, American Sociological Review, 82(6), pp. 1139–1166.
Charles Rahal
  • Load More

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

LCDS Logo

Footer

  • Home
  • About
  • People
  • Research
  • News

Funded by

Leverhulme trust

Leverhulme Centre for Demographic Science

42-43 Park End Street, Oxford OX1 1JD

twitter
youtube
youtube

© Leverhulme Centre for Demographic Science

|
Privacy Policy
|
Cookie Statement
|
Accessibility Statement