Prof Geoff Nicholls [photo]

Associate Professor of Statistics, University of Oxford
Tutor in Statistics and Tutor for Graduates, St Peter's College Oxford

I joined the CSML group in the Statistics Department here in Oxford in 2005 from the Math department
in Auckland in New Zealand. I was HOD here from 2012-2015. I have a college homepage at St Peters.

Contact details

Address: Department of Statistics, 24-29 St Giles, Oxford, OX1 3LG, UK
Phone: Dept +44-1865-282853; College +44-1865-278938
Email: nicholls@stats.ox.ac.uk
Office: Room 1.12
Maps: [Dept/College], [Streetview].

Research

Publications : Oxford CSML and Google Scholar

Keywords: Bayesian inference, approximation methods; misspecified models; Monte Carlo methods and calibration.

Current Research Students - DPhil & MSc:
Chris Carmona Model mispecification and big missing data
Jessie Jiang Statistical inference for partial orders
Hanwen Xing Calibration procedures for approximate Bayesian credible sets; Contrastive Learning
Schyan Zafar Non-parametric stochastic processes and time-evolving word meanings

Recent Graduates - DPhil:
Luke Kelly (2016) A stochastic Dollo model for lateral transfer: phylogenetics and lexical traits
Ross Haines (2016) Estimation of spatial fields and measurement locations: the Atlas of Late Middle English
Alexis Muir-Watt (2016) Inferring partial orders from random linear extensions: models for social hierarchy

Teaching and Supervision

I tutor Statistics and Probability in College where I am Tutor for Graduates. In the Statistics Department
I teach part of a module on Bayesian Inference in the StatML Doctoral training CDT, a Part C and MSc
course in Bayes Methods and parts of a Part B and MSc course in Computational Statistics. Here is a pointer
to these and other Department Courses. I also supervise Part C and MSc dissertations.

Recent Graduate Projects - MSc in Statistical Science, and MMath and MMathStats Part C
To be determined! (2021) Topics in Contrastive Learning
Alex Sauer (2020) Contrastive Learning and related likelihood-free methods for statistical inference
Olle Tieljooij (2020) Deep-learning statistical models for investment factors
Juha Kreula (2020) Spatio-temporal species distributions and presence-only data
Chunyi Luo, Hongyu Qian, Sam Field and Yuyang Shi (2020) Component-wise ABC and Random forest ABC
Xingyun Yu (2019) Applying Statistical Methods for RNA Profiling to Identify Body Fluid Type
Isabella Deutsch (2019) Bayesian Approaches to Meta-Analysis
Julia Xerri (2019) Inferring Patterns of Financial Product Ownership using Latent Models for Clustering
Oliver Cobb, Yiyi Xiao, Haoting Zhang and Kangning Zhang (2019) ABC model choice, calibration and summary statistics

Here are the term dates for the next few years.