Aaron Bostrom

2.6k total citations · 2 hit papers
7 papers, 1.4k citations indexed

About

Aaron Bostrom is a scholar working on Signal Processing, Plant Science and Ecology. According to data from OpenAlex, Aaron Bostrom has authored 7 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Signal Processing, 3 papers in Plant Science and 2 papers in Ecology. Recurrent topics in Aaron Bostrom's work include Time Series Analysis and Forecasting (4 papers), Smart Agriculture and AI (2 papers) and Music and Audio Processing (2 papers). Aaron Bostrom is often cited by papers focused on Time Series Analysis and Forecasting (4 papers), Smart Agriculture and AI (2 papers) and Music and Audio Processing (2 papers). Aaron Bostrom collaborates with scholars based in United Kingdom, China and United States. Aaron Bostrom's co-authors include Anthony Bagnall, Jason Lines, Eamonn Keogh, James Large, Jon Hills, Ji Zhou, Joshua Ball, Daniel Reynolds, Tao Cheng and Stephen D. Laycock and has published in prestigious journals such as New Phytologist, IEEE Transactions on Knowledge and Data Engineering and Plant Science.

In The Last Decade

Aaron Bostrom

7 papers receiving 1.4k 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 time series classification bake off: a review and experimental evaluation of recent algorithmic advances

2016 801 citations Anthony Bagnall, Jason Lines et al. Data Mining and Knowledge Discovery profile →
Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles

2015 277 citations Anthony Bagnall, Jason Lines et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aaron Bostrom United Kingdom	6	885	735	252	193	136	7	1.4k
Diego Furtado Silva Brazil	20	689 0.8×	786 1.1×	42 0.2×	145 0.8×	67 0.5×	54	1.5k
Vinícius M. A. Souza Brazil	14	373 0.4×	404 0.5×	43 0.2×	131 0.7×	22 0.2×	43	1.0k
Romain Tavenard France	11	275 0.3×	274 0.4×	25 0.1×	41 0.2×	57 0.4×	22	792
James Large United Kingdom	8	909 1.0×	750 1.0×	8 0.0×	202 1.0×	29 0.2×	8	1.3k
Bilson Campana United States	10	763 0.9×	493 0.7×	13 0.1×	133 0.7×	24 0.2×	15	1.1k
Alain Ketterlin France	6	348 0.4×	231 0.3×	12 0.0×	91 0.5×	40 0.3×	13	769
Miguel Lázaro-Gredilla Spain	17	187 0.2×	590 0.8×	37 0.1×	12 0.1×	87 0.6×	39	1.2k
Samuel Thomas United States	27	1.3k 1.5×	1.7k 2.3×	260 1.0×	8 0.0×	253 1.9×	110	2.4k
Brejesh Lall India	18	104 0.1×	167 0.2×	200 0.8×	25 0.1×	45 0.3×	237	1.5k
Eugene Tuv United States	10	506 0.6×	637 0.9×	8 0.0×	127 0.7×	23 0.2×	23	1.2k

Countries citing papers authored by Aaron Bostrom

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Aaron Bostrom

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

All Works

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7 of 7 papers shown

1.

Bostrom, Aaron, et al.. (2022). Multiple Imputation Ensembles for Time Series (MIE-TS). ACM Transactions on Knowledge Discovery from Data. 17(3). 1–28. 4 indexed citations

2.

O’Neill, Carmel M., Rachel Wells, Aaron Bostrom, et al.. (2020). SeedGerm: a cost‐effective phenotyping platform for automated seed imaging and machine‐learning based phenotypic analysis of crop seed germination. New Phytologist. 228(2). 778–793. 72 indexed citations

3.

Bostrom, Aaron, et al.. (2019). Combining computer vision and deep learning to enable ultra-scale aerial phenotyping and precision agriculture: A case study of lettuce production. Horticulture Research. 6(1). 70–70. 111 indexed citations

4.

Reynolds, Daniel, Frédéric Baret, Claude Welcker, et al.. (2018). What is cost-efficient phenotyping? Optimizing costs for different scenarios. Plant Science. 282. 14–22. 111 indexed citations

5.

Bagnall, Anthony, Jason Lines, Aaron Bostrom, James Large, & Eamonn Keogh. (2016). The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery. 31(3). 606–660. 801 indexed citations breakdown →

6.

Bagnall, Anthony, Jason Lines, Jon Hills, & Aaron Bostrom. (2016). Time-series classification with COTE: The collective of transformation-based ensembles. UEA Digital Repository (University of East Anglia). 46 indexed citations

7.

Bagnall, Anthony, Jason Lines, Jon Hills, & Aaron Bostrom. (2015). Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles. IEEE Transactions on Knowledge and Data Engineering. 27(9). 2522–2535. 277 indexed citations breakdown →

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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