Aaron Bostrom
Impact in
- Signal Processing top 0.5%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications
- Advanced Text Analysis Techniques
- Neural Networks and Applications
Papers in
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- Time Series Analysis and Forecasting 6
- Music and Audio Processing 2
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- Anomaly Detection Techniques and Applications 4
- Co-authors
- Anthony Bagnall (5 shared papers)Jason Lines (3 shared papers)Eamonn Keogh (1 shared paper)James Large (1 shared paper)Jon Hills (2 shared papers)Joshua Ball (3 shared papers)Ji Zhou (3 shared papers)Daniel Reynolds (2 shared papers)
- Journals
- New Phytologist (1 paper)Plant Science (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Horticulture Research (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Aaron Bostrom
9 papers receiving 1.7k citations
Aaron Bostrom's Hit Papers
Peers
Comparison fields: 5 of 121
- Signal Processing 1.1k
- Artificial Intelligence 934
- Economics and Econometrics 257
- Analytical Chemistry 76
- Plant Science 273
Countries citing papers authored by Aaron Bostrom
This map shows the geographic impact of Aaron Bostrom'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 Aaron Bostrom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron Bostrom more than expected).
Fields of papers citing papers by Aaron Bostrom
This network shows the impact of papers produced by Aaron Bostrom. 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 Aaron Bostrom. The network helps show where Aaron Bostrom may publish in the future.
Co-authors
The 24 scholars most cited alongside Aaron Bostrom, 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 time series classification bake off: a review and experimental evaluation of recent algorithmic advances Hit paper breakdown → | 2016 | 944 |
| 2 | Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles Hit paper breakdown → | 2015 | 317 |
| 3 | 2019 | 124 | |
| 4 | 2018 | 120 | |
| 5 | 2020 | 89 | |
| 6 | 2016 | 51 | |
| 7 | 2017 | 49 | |
| 8 | 2015 | 48 | |
| 9 | 2022 | 4 |
About Aaron Bostrom
Aaron Bostrom is a scholar working on Signal Processing, Artificial Intelligence, Economics and Econometrics, Plant Science and Ecology, having authored 9 papers that have together received 1.7k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (6 papers), Anomaly Detection Techniques and Applications (4 papers), Complex Systems and Time Series Analysis (4 papers), Remote Sensing in Agriculture (2 papers), Music and Audio Processing (2 papers), Smart Agriculture and AI (2 papers), Seed Germination and Physiology (1 paper) and Water Quality Monitoring Technologies (1 paper). The work is most often cited by research in Signal Processing (1.1k citations), Artificial Intelligence (934 citations), Economics and Econometrics (257 citations), Analytical Chemistry (76 citations) and Plant Science (273 citations). Aaron Bostrom has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Anthony Bagnall, Jason Lines, Eamonn Keogh, James Large, Jon Hills, Joshua Ball, Ji Zhou, Daniel Reynolds, Tao Cheng and Stephen D. Laycock. Their work appears in journals such as New Phytologist, Plant Science, IEEE Transactions on Knowledge and Data Engineering, Horticulture Research and ACM Transactions on Knowledge Discovery from Data.
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.