Mark Briers

1.5k total citations · 1 hit paper
27 papers, 873 citations indexed

About

Mark Briers is a scholar working on Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering. According to data from OpenAlex, Mark Briers has authored 27 papers receiving a total of 873 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 5 papers in Control and Systems Engineering. Recurrent topics in Mark Briers's work include Target Tracking and Data Fusion in Sensor Networks (18 papers), Distributed Sensor Networks and Detection Algorithms (6 papers) and Fault Detection and Control Systems (5 papers). Mark Briers is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (18 papers), Distributed Sensor Networks and Detection Algorithms (6 papers) and Fault Detection and Control Systems (5 papers). Mark Briers collaborates with scholars based in United Kingdom, Canada and Australia. Mark Briers's co-authors include Simon Maskell, Randal Douc, Chris Wymant, Michelle Kendall, Christophe Fraser, Luca Ferretti, Chris Holmes, Lucie Abeler‐Dörner, Dustin Lang and David Bonsall and has published in prestigious journals such as Nature, Information Fusion and Journal of the Royal Statistical Society Series C (Applied Statistics).

In The Last Decade

Mark Briers

27 papers receiving 812 citations

Hit Papers

The epidemiological impact of the NHS COVID-19 app 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The epidemiological impact of the NHS COVID-19 app
    2021 163 citations Chris Wymant, Luca Ferretti et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mark Briers United Kingdom 14 480 184 140 128 120 27 873
Hideo Hirose Japan 19 128 0.3× 107 0.6× 42 0.3× 89 0.7× 42 0.3× 131 1.2k
Nick J. Pizzi Canada 18 273 0.6× 173 0.9× 62 0.4× 55 0.4× 35 0.3× 72 822
Jamal Hussain India 15 482 1.0× 91 0.5× 518 3.7× 60 0.5× 218 1.8× 47 1.4k
Hongping Hu China 18 278 0.6× 36 0.2× 26 0.2× 162 1.3× 97 0.8× 56 934
Nino Antulov-Fantulin Switzerland 12 120 0.3× 67 0.4× 77 0.6× 27 0.2× 60 0.5× 33 584
Russell Cheng United Kingdom 21 253 0.5× 20 0.1× 44 0.3× 66 0.5× 41 0.3× 92 1.9k
Bruno Caprile Italy 11 166 0.3× 251 1.4× 48 0.3× 13 0.1× 122 1.0× 23 1.1k
Mustafa Mamat Malaysia 18 222 0.5× 29 0.2× 25 0.2× 85 0.7× 190 1.6× 202 1.4k
Jyh-Horng Jeng Taiwan 18 476 1.0× 75 0.4× 84 0.6× 57 0.4× 7 0.1× 70 1.1k
Osman Yağan United States 18 124 0.3× 36 0.2× 643 4.6× 163 1.3× 60 0.5× 85 1.4k

Countries citing papers authored by Mark Briers

Since Specialization
Citations

This map shows the geographic impact of Mark Briers's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mark Briers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Briers more than expected).

Fields of papers citing papers by Mark Briers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Briers. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mark Briers. The network helps show where Mark Briers may publish in the future.

Co-authorship network of co-authors of Mark Briers

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Briers. A scholar is included among the top collaborators of Mark Briers based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mark Briers. Mark Briers is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ferretti, Luca, Chris Wymant, Michelle Kendall, et al.. (2023). Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts. Nature. 626(7997). 145–150. 28 indexed citations
2.
Lomax, James W., et al.. (2022). Bayesian Imputation of COVID-19 Positive Test Counts for Nowcasting Under Reporting Lag. Journal of the Royal Statistical Society Series C (Applied Statistics). 71(4). 834–860. 5 indexed citations
3.
Wymant, Chris, Luca Ferretti, Lucie Abeler‐Dörner, et al.. (2021). The epidemiological impact of the NHS COVID-19 app. Nature. 594(7863). 408–412. 163 indexed citations breakdown →
4.
Kendall, Michelle, Luke Milsom, Lucie Abeler‐Dörner, et al.. (2020). Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis. The Lancet Digital Health. 2(12). e658–e666. 56 indexed citations
5.
Briers, Mark, et al.. (2014). Efficient data structures for large scale tracking. International Conference on Information Fusion. 1–8. 2 indexed citations
6.
Briers, Mark, et al.. (2009). Approximate Bayesian Computation for Source Term Estimation. 11 indexed citations
7.
Briers, Mark, Randal Douc, & Simon Maskell. (2009). Smoothing algorithms for state–space models. Annals of the Institute of Statistical Mathematics. 62(1). 61–89. 165 indexed citations
8.
Ebden, Mark, Mark Briers, & Stephen Roberts. (2008). Decentralized predictive sensor allocation. 1702–1707. 4 indexed citations
9.
Douc, Randal, et al.. (2006). Efficient Block Sampling Strategies for Sequential Monte Carlo Methods. Journal of Computational and Graphical Statistics. 15(3). 693–711. 85 indexed citations
10.
Briers, Mark, et al.. (2006). Fast particle smoothing. 481–488. 108 indexed citations
11.
Maskell, Simon, et al.. (2005). Tracking using a radar and a problem specific proposal distribution in a particle filter. IEE Proceedings - Radar Sonar and Navigation. 152(5). 315–322. 13 indexed citations
12.
Maskell, Simon, Richard G. Everitt, R.W. Wright, & Mark Briers. (2005). Multi-target out-of-sequence data association: Tracking using graphical models. Information Fusion. 7(4). 434–447. 28 indexed citations
13.
Briers, Mark, Randal Douc, & Sumeetpal S. Singh. (2005). Sequential auxiliary particle belief propagation. 8 pp.–8 pp.. 39 indexed citations
14.
Vermaak, J., Simon Maskell, & Mark Briers. (2005). A unifying framework for multi-target tracking and existence. 9 pp.–9 pp.. 24 indexed citations
15.
16.
Maskell, Simon, Richard G. Everitt, R.W. Wright, & Mark Briers. (2004). Multi-target out-of-sequence data association. CentAUR (University of Reading). 10 indexed citations
17.
Rutten, Mark, Simon Maskell, Mark Briers, & Neil Gordon. (2004). <title>Multipath track association for over-the-horizon radar using Lagrangian relaxation</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 12 indexed citations
18.
Maskell, Simon, Mark Briers, & R.W. Wright. (2004). <title>Fast mutual exclusion</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5428. 526–536. 15 indexed citations
19.
Briers, Mark, et al.. (2003). <title>Two-dimensional assignment with merged measurements using Langrangrian relaxation</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5204. 283–292. 5 indexed citations
20.
Briers, Mark, Simon Maskell, & Rebecca Wright. (2003). A rao-blackwellised unscented Kalman filter. 55–61. 36 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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