Matthew Middlehurst

1.0k total citations · 2 hit papers
9 papers, 447 citations indexed

About

Matthew Middlehurst is a scholar working on Signal Processing, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Matthew Middlehurst has authored 9 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Signal Processing, 6 papers in Artificial Intelligence and 5 papers in Economics and Econometrics. Recurrent topics in Matthew Middlehurst's work include Time Series Analysis and Forecasting (9 papers), Anomaly Detection Techniques and Applications (6 papers) and Complex Systems and Time Series Analysis (5 papers). Matthew Middlehurst is often cited by papers focused on Time Series Analysis and Forecasting (9 papers), Anomaly Detection Techniques and Applications (6 papers) and Complex Systems and Time Series Analysis (5 papers). Matthew Middlehurst collaborates with scholars based in United Kingdom, Germany and Spain. Matthew Middlehurst's co-authors include Anthony Bagnall, James Large, Michael Flynn, Patrick Schäfer, David Guijo-Rubio, Germain Forestier, Diego Furtado Silva, Chang Wei Tan and Geoffrey I. Webb and has published in prestigious journals such as Data Mining and Knowledge Discovery, Knowledge and Information Systems and UEA Digital Repository (University of East Anglia).

In The Last Decade

Matthew Middlehurst

9 papers receiving 443 citations

Hit Papers

align trajectories

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.

The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances

2020 285 citations Michael Flynn, James Large et al. Data Mining and Knowledge Discovery profile →
Bake off redux: a review and experimental evaluation of recent time series classification algorithms

2024 58 citations Matthew Middlehurst, Patrick Schäfer et al. Data Mining and Knowledge Discovery profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew Middlehurst United Kingdom	5	312	271	70	50	37	9	447
Maciej Łuczak Poland	9	298 1.0×	256 0.9×	84 1.2×	33 0.7×	32 0.9×	18	445
Michael Flynn United Kingdom	2	194 0.6×	190 0.7×	37 0.5×	40 0.8×	24 0.6×	2	337
Mohammad Shokoohi-Yekta United States	5	241 0.8×	200 0.7×	39 0.6×	44 0.9×	51 1.4×	8	378
Zhihan Yue China	3	190 0.6×	208 0.8×	18 0.3×	25 0.5×	35 0.9×	4	360
Tianmeng Yang China	3	190 0.6×	212 0.8×	18 0.3×	25 0.5×	36 1.0×	5	362
Lexiang Ye United States	5	699 2.2×	537 2.0×	195 2.8×	49 1.0×	95 2.6×	7	875
Jon Hills United Kingdom	6	808 2.6×	663 2.4×	221 3.2×	64 1.3×	81 2.2×	6	963
Youqiang Sun China	9	95 0.3×	103 0.4×	35 0.5×	17 0.3×	36 1.0×	16	288
Lifeng Shen China	10	176 0.6×	372 1.4×	15 0.2×	17 0.3×	37 1.0×	11	449
A.C. Lindgren United States	8	163 0.5×	140 0.5×	23 0.3×	18 0.4×	26 0.7×	8	302

Countries citing papers authored by Matthew Middlehurst

Since Specialization

Citations

This map shows the geographic impact of Matthew Middlehurst'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 Matthew Middlehurst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Middlehurst more than expected).

Fields of papers citing papers by Matthew Middlehurst

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Middlehurst. 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 Matthew Middlehurst. The network helps show where Matthew Middlehurst may publish in the future.

Co-authorship network of co-authors of Matthew Middlehurst

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Middlehurst. A scholar is included among the top collaborators of Matthew Middlehurst 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 Matthew Middlehurst. Matthew Middlehurst is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Middlehurst, Matthew, Patrick Schäfer, & Anthony Bagnall. (2024). Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery. 38(4). 1958–2031. 58 indexed citations breakdown →

2.

Bagnall, Anthony, Matthew Middlehurst, Germain Forestier, et al.. (2024). A Hands-on Introduction to Time Series Classification and Regression. ePrints Soton (University of Southampton). 6410–6411. 2 indexed citations

3.

Middlehurst, Matthew, Patrick Schäfer, & Anthony Bagnall. (2024). Correction: Bake off redux: a review and experimental evaluation of recent time series classification algorithms. Data Mining and Knowledge Discovery. 38(6). 4236–4237. 6 indexed citations

4.

Guijo-Rubio, David, et al.. (2024). Unsupervised feature based algorithms for time series extrinsic regression. Data Mining and Knowledge Discovery. 38(4). 2141–2185. 2 indexed citations

5.

Middlehurst, Matthew, Patrick Schäfer, & Anthony Bagnall. (2023). Bake off redux: a review and experimental evaluation of recent time series classification algorithms. arXiv (Cornell University). 4 indexed citations

6.

Middlehurst, Matthew, et al.. (2023). A review and evaluation of elastic distance functions for time series clustering. Knowledge and Information Systems. 66(2). 765–809. 27 indexed citations

7.

Middlehurst, Matthew, et al.. (2022). A Review and Evaluation of Elastic Distance Functions for Time Series Clustering. arXiv (Cornell University). 1 indexed citations

8.

Flynn, Michael, et al.. (2020). The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery. 35(2). 401–449. 285 indexed citations breakdown →

9.

Middlehurst, Matthew, James Large, & Anthony Bagnall. (2020). The Canonical Interval Forest (CIF) Classifier for Time Series Classification. UEA Digital Repository (University of East Anglia). 188–195. 62 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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