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



Alessandro Barp

Assistant Professor


François-Xavier Briol

Associate Professor


Jeremias Knoblauch

Assistant Professor
EPSRC Fellow

Postdoctoral Researchers

PhD Students


Oscar Key

PhD Student


Yann McLatchie

PhD Student


Masha Naslidnyk

PhD Student


Ilina Yozova

PhD Student

Visiting Researchers


Xing Liu

PhD Student


Saifuddin Syed

Florence Nightingale Bicentennial Fellow


Ayush Bharti

Visitor, Autumn 2022

Kaiyu Li

PhD, 2019-2024

Zhuo Sun

PhD, 2019-2023

Veit Wild

Visitor, Autumn 2023


One paper accepted at UAI 2024 on the topic of Bayesian quadrature for computing parametric expectations.
Two papers accepted at ICML 2024. The papers are both on the topic of scalable generalised Bayes, one in the context of Gaussian processes, and the other in the context of Kalman filtering.
Many members of the group attend and present at the ‘Functional inference and machine intelligence’ workshop at the University of Bristol.
Iman Simo-Dzumgang joins the group as a PhD student co-supervised by Dr. F-X Briol and Dr. Jeremias Knoblauch.
Kaiyu Li is awarded the James Nelson Prize for her paper on ‘Multilevel Bayesian quadrature’. This award is for the best paper published during the preceding year by a research student registered in the Department of Statistical Science at UCL.

Recent Publications

Major Research Funding

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)


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