About us
The Fundamentals of Statistical Machine Learning group is a research group in the UCL Department of Statistical Science. Our focus is on the intersection of statistical inference and machine learning methodology and theory.
Meet the Team
Faculty
Alessandro Barp
Assistant Professor
François-Xavier Briol
Professor of Statistics and Machine Learning
Jeremias Knoblauch
Associate Professor
Louis Sharrock
Assistant Professor
Postdoctoral Researchers
Harita Dellaporta
Postdoctoral Researcher
Masha Naslidnyk
Postdoctoral Researcher
PhD Students
Abdelhamid Ezzerg
PhD Student
Arina Odnoblyudova
PhD Student
Can Rager
PhD Student
Guilherme Pedrilho Soares
PhD Student
Matias Altamirano
PhD Student
William Laplante
PhD Student
Yann McLatchie
PhD Student
Ahab Isaac
PhD Student
Zixiao Hu
PhD Student
Zonghao (Hudson) Chen
PhD Student
Visiting Researchers
Sophia Kang
Visiting Researcher
Yuga Hikida
Visiting Researcher
Yuta Ono
Visiting Researcher
Alumni
Ayush Bharti
Visitor, Autumn 2022
Ieva Kazlauskaitė
IMSS Fellow, 2023-2024
Ilina Yozova
PhD, 2021-2026
Joshua Rooijakkers
Visitor 2025
Kaiyu Li
PhD, 2019-2024
Oscar Key
PhD, 2020-2025
Takuo Matsubara
Visitor, 2019-2023
Veit Wild
Visitor, Autumn 2023
Xing Liu
Visitor, 2023-2024
Zhuo Sun
PhD, 2019-2023
News
Yuta Ono joins the group as a visiting researcher. Yuta will be doing his PhD with Yingzhen Li at Imperial College London, and will be co-supervised by F-X.
Louis is co-organising a workshop on Non-Equilibrium Sampling — Diffusions, Flows, Particles to be held at Newcastle University on 2–4 September 2026. You can register your interest for the workshop here.
Four papers from the group accepted at ICML 2026:
- Stationary MMD points
- Thinned mean field Langevin dynamics
- Robust Bayesian optimisation with unbounded corruptions
- TabMGP: Martingale posterior with TabPFN
Louis and F-X are co-organisers of the Pre-ICML @ London 2026 event, which brings together members of the London machine learning community for a day of talks and posters.
Recent Publications
(2026).
Robust Bayesian Optimisation with Unbounded Corruptions.
In ICML 2026.
(2026).
TabMGP: Martingale posterior with TabPFN.
In ICML 2026.
(2025).
Multilevel neural simulation-based inference.
In NeurIPS 2025.
(2025).
Stationary MMD Points.
In ICML 2026.
(2025).
Kernel Quantile Embeddings and Associated Probability Metrics.
In ICML.
Major Research Funding
UCL EPSRC-funded Post-doctoral Extension Award. Project on “Reliable Insights from Scientific Simulators” (PI: Dellaporta)
Turing Project: “Bayesian Robustness in Filtering Algorithms” (PI: Briol)
Bloomberg Data Science Ph.D. Fellowship Program (PI: Altamirano)
EPSRC New Investigator Award. Project on ‘Transfer Learning for Monte Carlo Methods’ (PI: Briol)
EPSRC Small Grant in the Mathematical Sciences, Project on “Robust Foundations for Bayesian Inference” (PI: Briol, co-I: Knoblauch)
UKRI/Turing Project “Digital Twin Handbook” (co-I: Briol)
EP/W005859/1: EPSRC Fellowship, Project on “Optimisation-centric Generalisations of Bayesian Inference” (PI: Knoblauch)
Biometrika fellowship: “Generalising Bayesian Inference” (PI: Knoblauch)
Amazon Research Award: Project on “Transfer Learning for Numerical Integration in Expensive Machine Learning Systems” (PI: Briol)
Contact
- 1-19 torrington place, London, WC1E 7HB