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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

Li, D. et al. (2026) “De-Linearizing Agent Traces: Bayesian Inference of Latent Partial Orders for Efficient Execution”, arXiv.
Sun, S., Nicholls, G. and Lee, J. (2026) “Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation”, arXiv.
Battaglia, L. et al. (2025) “Amortising over hyperparameters in Generalised Bayesian Inference”, arXiv.
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.”

Contact Details

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

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