World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
48
Citations
14512
World Ranking
1182
National Ranking
91

Engineering and Technology

D-Index
46
Citations
12930
World Ranking
5043
National Ranking
332

Overview

Paul Fearnhead is affiliated with Lancaster University in the United Kingdom. Their research spans the intersecting fields of Mathematics and Computer Science with a primary focus on Statistics and Probability as well as Artificial Intelligence. The scientist's work addresses various subfields including Statistics, Probability and Uncertainty, Signal Processing, and Molecular Biology.

The core topics in their research involve Statistical Methods and Inference, Markov Chains and Monte Carlo Methods, Bayesian Methods and Mixture Models, Anomaly Detection Techniques and Applications, Advanced Statistical Process Monitoring, Time Series Analysis and Forecasting, and Advanced Statistical Methods and Models.

Fearnhead has contributed to multiple academic venues with frequent publications in the following:

  • arXiv (Cornell University)
  • Statistics and Computing
  • Journal of the American Statistical Association
  • Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • Journal of Statistical Software

The scientist has collaborated regularly with several co-authors, including:

  • Idris A. Eckley
  • Gaetano Romano
  • Guillem Rigaill
  • Kes Ward
  • Lorenzo Rimella

Selected recent papers authored or co-authored by Paul Fearnhead include:

  • Relating and comparing methods for detecting changes in mean, 2020, Stat
  • Stochastic Gradient Markov Chain Monte Carlo, 2020, Journal of the American Statistical Association
  • Testing for a Change in Mean after Changepoint Detection, 2022, Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise, 2020, arXiv (Cornell University)
  • Innovative and Additive Outlier Robust Kalman Filtering With a Robust Particle Filter, 2021, IEEE Transactions on Signal Processing

In addition to articles, Paul Fearnhead has contributed to book publications, including a forthcoming title:

  • Scalable Monte Carlo for Bayesian Learning, to be published by Cambridge University Press in 2025

Best Publications

  • Optimal Detection of Changepoints With a Linear Computational Cost

    Rebecca Killick;Paul Fearnhead;Idris Eckley

  • Improved particle filter for nonlinear problems

    J. Carpenter;P. Clifford;P. Fearnhead

  • Genome-wide association study of prostate cancer identifies a second risk locus at 8q24

    Meredith Yeager;Nick Orr;Richard B Hayes;Kevin B Jacobs

  • Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation

    Paul Fearnhead;Dennis Prangle

  • Exact and efficient Bayesian inference for multiple changepoint problems

    Paul Fearnhead

  • Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)

    Alexandros Beskos;Omiros Papaspiliopoulos;Gareth O. Roberts;Paul Fearnhead

  • Estimating recombination rates from population genetic data.

    Paul Fearnhead;Peter Donnelly

  • On-line inference for multiple changepoint problems

    Paul Fearnhead;Zhen Liu

  • An improved particle filter for non-linear problems

    J Carpenter;Peter Clifford;Paul Fearnhead

  • The Zig-Zag process and super-efficient sampling for Bayesian analysis of big data

    Joris Bierkens;Paul Fearnhead;Gareth O. Roberts

  • On-Line Inference for Hidden Markov Models via Particle Filters.

    Paul Fearnhead;Peter Clifford

  • Markov chain Monte Carlo, Sufficient Statistics, and Particle Filters

    Paul Fearnhead

  • On optimal multiple changepoint algorithms for large data

    Robert Maidstone;Toby Hocking;Guillem Rigaill;Paul Fearnhead

  • Particle filters for mixture models with an unknown number of components

    Paul Fearnhead

  • Particle filters for partially observed diffusions

    Paul Fearnhead;Omiros Papaspiliopoulos;Gareth O. Roberts

  • A sequential smoothing algorithm with linear computational cost.

    Paul Fearnhead;David Wyncoll;Jonathan Tawn

  • Analysis of changepoint models.

    Idris A. Eckley;Paul Fearnhead;Rebecca Killick

  • Spatial epidemiology and natural population structure of Campylobacter jejuni colonizing a farmland ecosystem.

    Nigel French;Mishele Barrigas;Patrick Brown;Paola Ribiero

  • Changepoint Detection in the Presence of Outliers

    Paul Fearnhead;Guillem Rigaill

  • Exact Bayesian curve fitting and signal segmentation

    P. Fearnhead

  • Approximate likelihood methods for estimating local recombination rates

    Paul Fearnhead;Peter Donnelly

Frequent Co-Authors

Gareth O. Roberts
Gareth O. Roberts University of Warwick
Nigel P. French
Nigel P. French Massey University
Emily B. Fox
Emily B. Fox Stanford University
Lyudmila Mihaylova
Lyudmila Mihaylova University of Sheffield
Peter Donnelly
Peter Donnelly University of Oxford
Guillaume Bourque
Guillaume Bourque McGill University
Andrew J. Fox
Andrew J. Fox Manchester Royal Infirmary
Andrew S. Fox
Andrew S. Fox University of California, Davis
Daniela Witten
Daniela Witten University of Washington
Daniel J. Wilson
Daniel J. Wilson University of Oxford

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students exploring Mathematics in the USA, branching into related fields can enhance career opportunities. One popular option is finance, where analytical skills are highly valued. Those interested can discover options like the cheapest online master's in finance, offering flexible and affordable paths for advanced study.

If you're aiming for leadership roles in business, pursuing an MBA can complement your mathematical expertise. Many professionals opt for a quickest online MBA degree program to accelerate their education while balancing work commitments.

Marketing is another promising area, especially with the rise of digital platforms. A focused MS in digital marketing degree cost USA is a practical choice to build knowledge in data-driven marketing strategies and analytics, linking well with a math background.

For those looking to fast-track their business education, considering 1 year MBA programs can provide intensive, streamlined learning. These programs often combine quantitative skills and business acumen, preparing graduates for diverse career paths efficiently.

Best Scientists Citing Paul Fearnhead

Trending Scientists