Curriculum Vitae

Contact Information

Research Interests

Methodology: Spatial statistics, spatiotemporal statistics, gradient estimation & wombling, functional data analysis, functional phase registration, elastic data analysis, distributional data analysis, robust statistics.

Application: Official statistics, public policy, epidemiology (in particular Covid‑19), excess mortality statistics, prices econometrics (in particular house prices).

Employment

Post-Doctoral Researcher, Humboldt-Universität zu Berlin, 2026–29

• Topic: Flexible regression methods for curve and shape data.
• Supervisor: Professor Sonja Greven, Chair of Statistics.
• Funding: DFG grant.

Research Internship, University of Cambridge, 2021

• Topic: Bayesian inversion in positron emission tomography.
• Supervisor: Dr Sergio Bacallado.
• Funding: Trinity College Summer Studentship Award.

Education

PhD, Pure Mathematics and Mathematical Statistics, University of Cambridge, 2022–26

• Specialism: Developing novel models and methodologies to understand official statistics and answer public policy questions—including for spatial and functional data—with an eye on robust estimation.
• Supervisor: Professor Sir John A. D. Aston, Harding Professor for Statistics in Public Life and former Chief Scientific Advisor at the UK's Home Office.
• Funding: Harding Professorship Trust Fund.

MMath, Mathematics Part III, University of Cambridge, 2021–22

• Specialism: Statistics and Information Theory, including robust statistics and functional data analysis.
• Dissertation: “An International Comparison of Deaths”, supervised by Professor Sir John A. D. Aston.

BA, Mathematical Tripos Parts I and II, University of Cambridge, 2018–21; and MA, 2025

Cambridge University Language Programme Award in Advanced Spanish (CEFR C1), 2018–19

Teaching

Postgraduate Drop-In Sessions, University of Cambridge, 2022–25
Part III Drop-In Sessions are hour-long sessions where postgraduate mathematicians at the University of Cambridge may approach a postgraduate student with questions about a course they're attending.

• Part III Functional Data Analysis: Definition of functional data, functional principal component analysis, registration, covariance operators, functional linear models.
• Part III Robust Statistics: Asymptotic theory of M-estimators and minimax results, influence functions, optimal robust estimators, robust linear regression, robust hypothesis testing, estimation under adversarial contamination, heavy-tailed estimation.
• Part III Statistical Learning in Practice: GLMs for regression and classification, model selection and regularisation, Bayesian regression, mixed effects models, linear discriminant analysis and SVMs, deep learning and random forests, PCA, time series.

Undergraduate Supervisor, University of Cambridge, 2022–25
Supervisions are a form of teaching at the University of Cambridge where—in general, in Mathematics—a supervisor and two undergraduates meet for an hour to work through example questions from each lectured course.

• Part II Principles of Statistics: The likelihood principle, Bayesian inference, decision theory, multivariate analysis, nonparametric inference and Monte Carlo techniques.
• Part IB Statistics: Estimation, hypothesis testing, linear models.

Papers

In Preparation

• Luke A. Barratt and John A. D. Aston. “School Inspections and House Prices: Distributional Function-on-Function Regression for Spatial Data.”
• Luke A. Barratt and John A. D. Aston. “Spatially Indexed Distribution Analysis as Applied to House Prices in the UK.”

Pre-Prints

Accepted Manuscripts

• Luke A. Barratt and John A. D. Aston. “A Nonparametric and Functional Wombling Methodology.” February 2026. Spatial Statistics.
• Luke A. Barratt and John A. D. Aston. “Exploring Covid‑19 Spatiotemporal Dynamics: Non‑Euclidean Spatially Aware Functional Registration.” December 2025. Annals of Applied Statistics.
• Luke A. Barratt. “Luke Barratt's Contribution to the Discussion of 'Some Statistical Aspects of the Covid-19 Response' by Wood et al.” July 2025. Journal of the Royal Statistical Society: Series A.

Talks

• December 2026; Berlin, Germany. Invited Talk: Title TBD. In Organised Session: "Complex Functional Data." CMStat 2026. Luke A. Barratt.
• August 2026; Athens, Greece. Invited Talk: "Schools and House Prices: Spatiotemporal Regression of Quantile Functions on Categorical Covariates." In Organised Session: "Advances in Distributional Data Analysis." CompStat 2026. Based on work by Luke A. Barratt and John A. D. Aston..
• Saturday 23 August 2025; Tokyo, Japan. Contributed Talk: “Spatially Indexed Distribution Analysis as Applied to House Prices in the UK.” EcoSta 2025. Based on work by Luke A. Barratt and John A. D. Aston
• Monday 5 August 2024; Portland OR, United States. Contributed Talk: “Spatially Aware Temporal Registration of Covid Waves.” JSM 2024. Based on work by Luke A. Barratt and John A. D. Aston.
• Tuesday 5 September 2023; Harrogate, United Kingdom. Rapid-Fire Talk: “A Novel Approach to Spatially Indexed Functional Data Analysis.” RSS International Conference 2023. Based on work by Luke A. Barratt and John A. D. Aston.

Coding Languages

I am proficient in R (including writing packages), Python, and MATLAB, and I am familiar with C++, SQL, and Mathematica.

Other Activities

• First and Third Trinity Boat Club Committee, 2019–26: Novice Captain, Lower Boats Captain, Secretary, Men's Captain, Overall Captain, Alumni Relations Officer.
• Cambridge University Combined Boat Clubs, 2022–26: Events Secretary and Co-Opted Executive Member.