Professor Geoff Nicholls

Prof Nicholls teaches probability, statistics and applied mathematics. He is interested in developing new methodology and algorithms for statistical inference. He provides mathematical support for scientific research in a wide range of fields.

Since 2015, he has developed new methodology in Statistical Machine Learning and Computational Statistics. His recent research is motivated by ongoing collaboration with researchers in archaeology, business inventory management, environmetrics, finance, genetics, history and philology, and by questions arising from satellite imaging data, geothermal reservoir imaging, ecology, social network analysis and historical linguistics.

Selected publications

Nicholls, GK, Lee, JE, Karn, N, Johnson, D, Huang, R and Muir-Watt, A, “Bayesian inference for partial orders from random linear extensions: Power relations from 12th century royal acta”, Annals of Applied Statistics, 19(2), 1663-1690, (2025)

Zafar, S and Nicholls, GK, “An embedded diachronic sense change model with a case study from ancient Greek”, Comp. Stats. & Data Analysis, 199:108011 (2024)

Jiang, C, Nicholls, GK, and Lee, JE, “Bayesian inference for vertex-series-parallel partial orders”, Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR:216:995–1004. (2023)

Zafar, S and Nicholls, GK, “Measuring diachronic sense change: new models and Monte Carlo methods for Bayesian inference”, J. Roy. Statist. Soc. Series C, Applied Statistics, 71(5):1569-1604, (2022)

Hu, R, Nicholls, GK, and Sejdinovic, D, “Large Scale Tensor Regression using Kernels and Variational Inference”, Machine Learning, 111, 2663–2713 (2022)

Styring, AK., Carmona, CU., Isaakidou, V., Karathanou, A., Nicholls, GK., Sarpaki, A., & Bogaard, A, “Urban form and scale shaped the agroecology of early ‘cities’ in northern Mesopotamia, the Aegean and Central Europe”, Journal of Agrarian Change, 22(4):831– 854, (2022)

Xing, H, Nicholls, GK and Lee, JE, “Distortion estimates for approximate Bayesian inference”, Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR124:1208-1217, (2020)

Roeling, MP, Nicholls GK, “Imputation of attributes in networked data using Bayesian Autocorrelation Regression Models”, Social Networks, 62:24-32 (2020)

Moores, MT, Nicholls, GK, Pettitt, AN, and Mengersen, K, “Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model”, Bayesian Analysis 15:1–27 (2020)

Carmona, CU and Nicholls, GK, “Semi-Modular Inference”, International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR108:4226-4235, (2020)