CV
Contact Information
| lab85@cam.ac.uk | |
| Post | Trinity College, Cambridge, CB2 1TQ, United Kingdom |
| Phone | +44 (0)7340 244083 |
| Office | D0.17, Centre for Mathematical Sciences, Wilberforce Road, Cambridge, CB3 0WB |
| Website | http://www.statslab.cam.ac.uk/~lab85/ |
Research Interests
Spatial statistics, functional data analysis, functional phase registration, dynamic spatiotemporal and functional modelling, robust statistics, official statistics, public policy, covid-19 statistics, excess mortality estimation.Education
TRINITY COLLEGE, UNIVERSITY OF CAMBRIDGE
PhD, Pure Mathematics and Mathematical Statistics, 2022–
- Specialism: Developing novel models and methodologies to understand official statistics and answer public policy questions, including for spatial and functional data, and with an eye on robust estimation.
- Supervisor: Professor Sir John AD 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, 2021–22
- Specialism: Statistics and Informtaion Theory, including Robust Statistics and Functional Data Analysis
- Dissertation: 'An International Comparison of Deaths', under the supervision of Professor Sir John AD Aston
Research Internship, 2021
- Topic: Bayesian inversion in positron emission tomography
- Supervisor: Dr Sergio Bacallado
BA, Mathematical Tripos Parts I and II, 2018–21
Cambridge University Language Programme Award in Advanced Spanish (CEFR C1), 2018–19
Teaching
Postgraduate Drop-In Sessions, Unviersity of Cambridge, 2022–
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 anlaysis, 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–
Supervisions are a form of teaching at the University of Cambridge where—in general, in Mathematics—a supervisor and two undergraduates sit down together for an hour to go through example questions in each lectured course. It is often touted by the University as a key selling point of their undergraduate courses.
- Part II Principles of Statistics: The likelihood principle, Bayesian inference, decision theory, multivariate analysis, nonparametric inference and Monte Carlo technqiues.
- Part IB Statistics: Estimation, hypothesis testing, linear models.
Conference Abstracts
- Luke A Barratt and John AD Aston. 'A Novel Approach to Spatially Indexed Functional Data Anlaysis.' Royal Statistical Society International Conference 2023.
Other Activities
- First and Third Trinity Boat Club Committee, 2019–: Novice Captain, Lower Boats Captain, Secretary, Men's Captain, Overall Captain, Alumni Relations Officer.