Professor Geoff Nicholls

Associate Professor of Statistics

New collaborations welcome!

Biographical Sketch

Professor Geoff Nicholls, B.Sc. (Physics, Canterbury, New Zealand), MA, PhD (DAMTP, Cambridge, UK), researches Bayesian statistical methodology and lectures in statistics in the Department. He teaches probability, statistics and applied mathematics in St Peter's college. Geoff joined the Statistics Department in 2005 from the Mathematics Department of the University of Auckland in New Zealand. He was Head of Department 2012-2015.

Research Interests

Applied Bayesian inference
Bayesian statistical methods
Computational statistics
Monte Carlo and Variational methods

Geoff is working on Bayesian statistical inference for problems with computationally demanding prior and likelihood evaluations. Research is driven by problems presented by scientists and scholars working in a range of application areas, including Geoscience, Linguistics, History and Sociology, Genetics and Archaeology. Solving these problems motivates new statistical models, well adapted computational tools and novel statistical methodology.

Publications

Lee, J., Liu, S. and Nicholls, G. (2025) “Bayesian inference for the learning rate in Generalised Bayesian inference”, arXiv.

Nicholls, G. et al. (2025) “Bayesian inference for partial orders from random linear extensions: Power relations from 12th century royal acta”, The Annals of Applied Statistics, 19(2), pp. 1663–1690.

Carmona, C. et al. (2024) “Simultaneous reconstruction of spatial frequency fields and sample locations via Bayesian semi-modular inference”, arXiv.

Zafar, S. and Nicholls, G. (2024) “Exploring learning rate selection in generalised Bayesian inference using posterior predictive checks”, arXiv.

Jiang and Nicholls, G. (2024) “Non-parametric Bayesian inference for partial orders with ties from rank data observed with Mallows noise”, arXiv.

Zafar, S. and Nicholls, G. (2024) “An embedded diachronic sense change model with a case study from ancient Greek”, Computational Statistics and Data Analysis, 199.

Zafar, S. and Nicholls, G. (2023) “An embedded diachronic sense change model with a case study from ancient Greek.”

Kelly, L. et al. (2023) “TraitLab: a Matlab package for fitting and simulating binary tree-like data”, arXiv.

Jiang, C., Nicholls, G. and Lee, J. (2023) “Bayesian inference for vertex-series-parallel partial orders”, in Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence. PMLR, pp. 995–1004.

Wu, C.-H., Roeder, A. and Nicholls, G. (2023) “Biclustering random matrix partitions with an application to classification of forensic body fluids.”

Contact Details

College affiliation: Fellow and Tutor at St Peter's College

Email: nicholls@stats.ox.ac.uk

Personal webpage

Office: 1.12

Research Students

Current DPhil students:

Sitong Liu Generalised Bayesian inference
Laura Battaglia Bayes methods for misspecified models
Holly Li Scalable Statistical inference for partial orders
Shiyi Sun New variational methods for Bayesian inference

Recent Graduates - DPhil:

Jessie Jiang (2024) Statistical inference for partial orders
Schyan Zafar (2024) Bayesian inference for multivariate time series
Chris Carmona (2023) Bayesian Semi-Modular Inference
Lorenzo Pacchiardi (2022) Statistical inference in generative models (with R Dutta)
Hanwen Xing (2022) Diagnostic Methods for Bayesian Inference

Research Groups

Statistical Theory and Methodology

Computational Statistics and Machine Learning