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
Associate Professor
Jeremias Knoblauch
Assistant Professor
EPSRC Fellow
PhD Students
Abdelhamid Ezzerg
PhD Student
Arina Odnoblyudova
PhD Student
Ilina Yozova
PhD Student
Iman Simo-Dzumgang
PhD Student
Masha Naslidnyk
PhD Student
Matias Altamirano
PhD Student
Oscar Key
PhD Student
William Laplante
PhD Student
Yann McLatchie
PhD Student
Zonghao (Hudson) Chen
PhD Student
Visiting Researchers
Saifuddin Syed
Florence Nightingale Bicentennial Fellow
Alumni
Ayush Bharti
Visitor, Autumn 2022
Ieva Kazlauskaitė
IMSS Fellow, 2023-2024
Kaiyu Li
PhD, 2019-2024
Veit Wild
Visitor, Autumn 2023
Xing Liu
Visitor, 2023-2024
Zhuo Sun
PhD, 2019-2023
News
Yann McLatchie will be starting as an Alan Turing Enrichment Scheme student starting October 2024.
Dr Jeremias Knoblauch has been promoted to Associate Professor. Congratulations!
Abdelhamid Ezzerg joins as a PhD student co-supervised by Jeremias Knoblauch and Ilija Bogunovic (Department of Electronic and Electrical Engineering).
William Laplante joins as a PhD student on the UCL Data Intensive Science CDT, supervised by F-X Briol and Andrew Duncan (Turing Institute).
Dr Ayush Bharti (Aalto University) awarded Academy of Finland Fellowship, including funding for a PhD student and several research visits at UCL to work with F-X Briol on simulation-based inference.
Recent Publications
(2024).
Conditional Bayesian Quadrature.
In UAI.
(2024).
Conformal Counterfactual Inference under Hidden Confounding.
in KDD 2024.
(2024).
Outlier-robust Kalman Filtering through Generalised Bayes.
In ICML.
(2024).
Robust and Conjugate Gaussian Process Regression.
In ICML.
(2024).
The Impact of Loss Estimation on Gibbs Measures.
In arXiv.
(2024).
Scalable Data Assimilation with Message Passing.
In Climate Informatics.
Major Research Funding
Turing Project: “Bayesian Robustness in Filtering Algorithms” (PI: Briol)
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