About
I am Professor of Statistics and Machine Learning (effective Oct 2025) at UCL Statistical Science, where I co-lead the Fundamentals of Statistical Machine Learning research group.
My research focuses on statistical and machine learning methodology, though I am also interested in applications in the sciences and engineering. My primary focus it the design of methods to merge large-scale scientific models with data, which requires the development of novel computational methods, inference methods that remain robust to model misspecification, and tools for uncertainty quantification.
At UCL, I am co-director (and scholar) of the UCL ELLIS unit, theme lead for Computational Statistics and Machine Learning (CSML) within the department of Statistical Science, and co-director of research of the CDT in Data-Intensive Science. Beyond UCL, I am also an elected board member for the CSML section of the Royal Statistical Society, an associate editor for the SIAM/ASA Journal on Uncertainty Quantification and Bayesian Analysis, and an area chair for AISTATS.
Prior to my current position, I did my bachelors and masters (MMORSE) at the University of Warwick, then a PhD through a joint CDT in statistics and machine learning at Warwick and Oxford. I then spent a year as a postdoctoral researcher, first in the Department of Mathematics at Imperial College London, then in the Department of Engineering at the University of Cambridge. I then joined UCL Statistical Science, where I was a lecturer (2019-2023) and then associate professor (2023-2025). From 2020-2023, I was also a Group Leader in Data-Centric Engineering at The Alan Turing Institute, the UK’s national institute for Data Science and AI.
For more details on my work, see my Google Scholar profile, or my Publications page, which points to a number of project pages highlighting different areas where I have made significant contributions. If you are a student/postdoc interested in working with me, please have a look at this page.
News
I have been promoted to Professor of Statistics and Machine Learning at UCL, effective 1st October 2025.
I will be giving a short-course on “Robust and scalable simulation-based inference” at Greek Stochastics 2025.
I will be visiting the Isaac Newton Institute’s programme on ‘representing, calibrating & leveraging prediction uncertainty from statistics to machine learning’ for part of July.
I have three papers accepted at ICML 2025 on topics from the computation of nested expectations, to kernel embeddings and robust spatio-temporal modelling.