麻豆传媒

Education/experience:

• I obtained an MSc (2011) and (2015) in Statistics from The University of Warwick;
• subsequently, I worked as a research associate at Cambridge, UCL, and NUS (Singapore);
• before joining 麻豆传媒, I was Lecturer in Statistics at Loughborough University.

Current administrative roles:

• lead
• PGR Selector for the Statistics Section;

Research interests:

I develop and analyse methodology for Computational (Bayesian) Statistics, especially in high dimensions, e.g.:

• conditional sequential Monte Carlo (CSMC) methods in high dimensions [, ],
• CSMC-type generalisations of MALA, MGRAD and PCN(L) which scale more favourably than standard versions of these algorithms with the time horizon in state-space models [],
• particle MCMC methods [, ].

I am also interested in applications of such methods in biology. For instance, I have been working on:

• ecology [, ],
• epigenetics (DNA methylation) []; our implementation is available as a Nextflow pipeline on .

Other research interests:

1. machine learning, in particular on machine unlearning;
2. mathematical and statistical modelling of endurance sports, e.g., running or cycling; some preliminary works are available here [journal, ] (see also the ) and here [].

More generally, I am always keen to collaborate across disciplines on projects that could benefit from statistical/mathematical modelling, data science, or machine learning. Also feel free to contact me if you are interested in PhD projects in any of the above-mentioned areas.

PhD students:

• (machine unlearning; supervised jointly with Prof. ; graduated 2024);
• Jonah Drake (statistical modelling of endurance sports; supervised jointly with Dr );
• Petros Andreou (machine unlearning; supervised jointly with Prof. );
• Jamie Lanyon (machine unlearning; supervised jointly with Prof. ).