Matthew Middlehurst
Impact in
- Signal Processing top 2%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications
- Advanced Text Analysis Techniques
- Neural Networks and Applications
Papers in
-
- Time Series Analysis and Forecasting 13
- Music and Audio Processing 7
- Data Management and Algorithms 1
-
- Complex Systems and Time Series Analysis 8
- Co-authors
- Anthony Bagnall (13 shared papers)James Large (3 shared papers)Michael Flynn (2 shared papers)Jason Lines (1 shared paper)David Guijo-Rubio (2 shared papers)Diego Furtado Silva (1 shared paper)Geoffrey I. Webb (1 shared paper)Germain Forestier (1 shared paper)
- Journals
- Data Mining and Knowledge Discovery (4 papers)Knowledge and Information Systems (1 paper)Lecture notes in computer science (4 papers)ArXiv.org (1 paper)ePrints Soton (University of Southampton) (1 paper)
- Partner nations
- United KingdomGermanySpain
In The Last Decade
Matthew Middlehurst
13 papers receiving 639 citations
Matthew Middlehurst's Hit Papers
Peers
Comparison fields: 5 of 100
- Signal Processing 473
- Artificial Intelligence 396
- Economics and Econometrics 107
- Management Science and Operations Research 42
- Computer Vision and Pattern Recognition 50
Countries citing papers authored by Matthew Middlehurst
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
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-authors
The 9 scholars most cited alongside Matthew Middlehurst, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances Hit paper breakdown → | 2020 | 332 |
| 2 | Bake off redux: a review and experimental evaluation of recent time series classification algorithms Hit paper breakdown → | 2024 | 79 |
| 3 | 2020 | 75 | |
| 4 | 2019 | 49 | |
| 5 | 2023 | 37 | |
| 6 | 2020 | 31 | |
| 7 | 2022 | 18 | |
| 8 | 2024 | 7 | |
| 9 | 2023 | 5 | |
| 10 | 2024 | 4 | |
| 11 | 2023 | 4 | |
| 12 | 2024 | 2 | |
| 13 | 2022 | 1 |
About Matthew Middlehurst
Matthew Middlehurst is a scholar working on Signal Processing, Economics and Econometrics, Artificial Intelligence, Infectious Diseases and Organic Chemistry, having authored 13 papers that have together received 644 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (13 papers), Complex Systems and Time Series Analysis (8 papers), Music and Audio Processing (7 papers), Anomaly Detection Techniques and Applications (7 papers) and Data Management and Algorithms (1 paper). The work is most often cited by research in Signal Processing (473 citations), Artificial Intelligence (396 citations), Economics and Econometrics (107 citations), Management Science and Operations Research (42 citations) and Computer Vision and Pattern Recognition (50 citations). Matthew Middlehurst has collaborated with scholars based in United Kingdom, Germany and Spain. Frequent co-authors include Anthony Bagnall, James Large, Michael Flynn, Jason Lines, David Guijo-Rubio, Diego Furtado Silva, Geoffrey I. Webb, Germain Forestier and Chang Wei Tan. Their work appears in journals such as Data Mining and Knowledge Discovery, Knowledge and Information Systems, Lecture notes in computer science, ArXiv.org and ePrints Soton (University of Southampton).
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.