About
Sam Power is a Lecturer in the School of Mathematics at the University of Bristol. He holds a PhD in Mathematics from the University of Cambridge (awarded January 2021) and an MMath. His research focuses on computational statistics, Monte Carlo methods, and probabilistic modeling.
Education
- PhD, University of Cambridge (30 Aug 2016 – 30 Jan 2021)
- MMath, University of Cambridge
Research Interests
Dr Power’s work lies at the intersection of probability theory, statistics, and machine learning. He investigates advanced Monte Carlo techniques including Markov Chain Monte Carlo (MCMC), particle methods, and piecewise-deterministic Markov processes. His recent projects explore convergence guarantees via functional inequalities such as Poincaré and log-Sobolev inequalities, state-space models for online learning, and uncertainty quantification.
Publication Trends
Across 20+ publications (2019–2025), Power has consistently advanced theoretical understanding and practical performance of sampling algorithms. Key themes include error bounds for particle and gradient-based methods, weak Poincaré inequalities, and applications in machine-learning systems such as online skill rating and Bayesian active learning.
Scientific Awards
- No awards explicitly listed in the provided material.
Students & Grants
- No explicit information on supervised students or funded grants is present.
Labs & Teams
Dr Power is affiliated with the School of Mathematics at Bristol; no specific laboratory or research group name is provided.
