I am a doctoral researcher at University College London in the Department of Statistical Science, supervised by Jeremias Knoblauch and Edwin Fong. Before this, I worked as a research assistant at Aalto University supervised by Aki Vehtari.
I am one of the organisers of the post-Bayes seminar series, the First workshop on Advances on post-Bayesian methods, and the OPTIMAL workshop at AISTATS 2026 in Tangier.
My research interests include developing theory and methodology for Bayesian prediction, and modernising prior elicitation. I have previously held data science positions at 7Bridges Ltd., GOGOX Ltd., and VoiceIQ Ltd.
I have previously acted as a reviewer for the Journal of the American Statistical Association, the Journal of Machine Learning Research, Bayesian Analysis, Statistics and Computing, and am open to review papers relating to any of the topics discussed above.
Bio
- 2023 -
- PhD candidate in Statistical Science UCL Supervised by Jeremias Knoblauch and Edwin Fong
- Research visits at HKU (hosted by Edwin Fong) and Sorbonne Université (hosted by Badr-Eddine Chérief-Abdellatif)
- 2021 - 2023
- MSc Machine Learning, Data Science, and Artificial Intelligence Aalto University Thesis on "Efficient estimation of selection-induced bias in Bayesian model selection," supervised by Aki Vehtari
- Research Assistant in agile probabilistic AI Aalto University Probabilistic Machine Learning (PML) group
- 2019 - 2020
- Year abroad studying Mathematics and Computer Science Université de Bordeaux
- 2017 - 2021
- BSc (Hons) Mathematics with a Modern Language (French) University of Manchester Thesis on "Graphical models for time series analysis," supervised by Jingsong Yuan and Korbinian Strimmer
Selected research
- "Predictively oriented posteriors." arXiv
- "Predictive performance of power posteriors." Biometrika. arXiv code blog talk
- "The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions." Bayesian Analysis. arXiv code blog
- "Efficient estimation and correction of selection-induced bias with order statistics." Statistics and Computing. arXiv code blog
- "Advances in projection predictive inference." Statistical Science. arXiv code blog
Software
I help develop the following software:- Kulprit
- Kullback-Leibler projections for Bayesian model selection author. code
- LOO
- Approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS) contributor. code
- Projpred
- Projection predictive feature selection contributor. code
- Bambi
- Bayesian model-building interface in Python contributor. code