Activities
Memberships
- Royal Statistical Society (RSS) Computational Statistics and Machine Learning (CSML) Section Committee Member.
Editorial & conference service
- Associate Editor for Statistics and Computing (2024 - ).
- Area Chair, International Conference on Learning Representations (ICLR) 2027.
Event organisation
- 2nd RSS/Turing CSML Section Workshop on Gradient Flows for Sampling, Inference, and Learning.
- Isaac Newton Institute (INI) Satellite Programme on Diffusions in Machine Learning
- Isaac Newton Institute (INI) Satellite Programme on Heavy Tails in Machine Learning
- RSS CSML Section Workshop on Gradient Flows for Sampling, Inference, and Learning. [Youtube videos]
- Turing Theory and Methods Challenge Fortnight (2022-2023), Accelerating Generative Models and Nonconvex Optimisation, [outputs].
- SMC Masterclass (organiser and lecturer), Bristol, UK, 2022.
Lectures
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Introduction to Bayesian filtering: theory & methods
Summer School on Bayesian filtering: fundamental theory and numerical methods (SSBF 2024). [lecture material], [video 1], [video 2]
- SMC Masterclass (organiser and lecturer), Bristol, UK, 2022, [notes], [Lecture 1], [Lecture 2].
Conference & workshop talks
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Efficient Stochastic Optimisation via Sequential Monte Carlo
13th Spain Workshop on Signal Processing, Information Theory and Communications.
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A multiscale approach to computational statistics
CMStatistics, 2025.
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Diffusion-based Learning of Latent Variable Models
Workshop on Recent Developments in Theoretical Machine Learning, Imperial College London.
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Tweedie Moment Projected Diffusion Models for Inverse Problems
Amazon StatML Workshop, Berlin, Germany.
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Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
Isaac Newton Institute, Generative Models for Inverse Problems Workshop, Cambridge, UK [video].
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Convergence Properties for Optimised Adaptive Importance Samplers
Invited speaker at the 5th Workshop on Sequential Monte Carlo Methods (SMC2022), Madrid.
Seminar talks
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Particle-based approaches to stochastic approximation: Progress and challenges
King's College London, Statistics Seminar.
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Particle-based approaches to stochastic approximation: Progress and challenges
London School of Economics, Statistics Seminar.
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Diffusion-based Maximum Marginal Likelihood Estimation: Overdamped, Accelerated, and Proximal
Data Analytics Seminar, ESSEC Business School, Paris.
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Diffusion-based Maximum Marginal Likelihood Estimation: Overdamped, Accelerated, and Proximal
Information Theory Seminar, University of Cambridge, [video]
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Interacting Particle Diffusions for Statistical Inference
SQUIDS Seminar, University of Manchester
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Diffusions for Statistical Inference and Inverse Problems
Southampton S3RI Seminar
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Diffusions for Statistical Inference and Inverse Problems
Imperial Statistics Seminar
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Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
University of Oxford, Statistics Seminar
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Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
University of Edinburgh, Statistics Seminar.