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Researcher · University of California, Riverside · United States

Eamonn Keogh

Eamonn Keogh publishes mostly in Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, on topics such as Time Series Analysis and Forecasting, Anomaly Detection Techniques and Applications and Data Management and Algorithms.

ORCID 0000-0002-4188-3968 OpenAlex
World rank
#9,582
of 7,710,434 ranked researchers
Rank in United States
#3,291
of 1,627,098
Works
404
Citations
45k
Citations per work
112.5
h-index
98
i10-index 248Top 0.1% in Signal Processing
Eamonn Keogh

What does Eamonn Keogh research?

Eamonn Keogh's work is mostly in Computer Science (80%), Economics, Econometrics and Finance (7%).

Physical Sciences: 322 works · 79.7% of their workComputer Science: 322 works · 79.7% of their workSignal Processing: 174 works · 43.0% of their workArtificial Intelligence: 87 works · 21.6% of their workComputer Vision and Pattern Recognition: 44 works · 10.8% of their workComputer Networks and Communications: 10 works · 2.4% of their workInformation Systems: 8 works · 1.9% of their workEverything else: 55 works · 13.7% of their workSocial Sciences: 27 works · 6.6% of their workEconomics, Econometrics and Finance: 27 works · 6.6% of their workEconomics and Econometrics: 27 works · 6.6% of their workTHEIR WORKEamonn Keogh404works
Physical Sciences80%Social Sciences7%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science32279.7%
  2. Everything else5513.7%
    1. Economics, Econometrics and Finance276.6%
  1. 1Signal Processing43% of their works
  2. 2Artificial Intelligence22% of their works
  3. 3Computer Vision and Pattern Recognition11% of their works
  4. 4Economics and Econometrics7% of their works
  5. 5Computer Networks and Communications2% of their works
  6. 6Information Systems2% of their works

Research topics

Which keywords describe Eamonn Keogh's research?

The keywords of their largest research topics: Deep Learning, Time Series, Feature Extraction, Clustering, Dynamic Time Warping, Neural Networks, Anomaly Detection and Unsupervised.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 20 words, with their numbers
  1. Deep Learning4903 topics
  2. Time Series4022 topics
  3. Feature Extraction3772 topics
  4. Clustering2891 topic
  5. Dynamic Time Warping2891 topic
  6. Neural Networks1612 topics
  7. Anomaly Detection1131 topic
  8. Unsupervised1131 topic
  9. GPS Trajectories941 topic
  10. Trajectory Data Mining941 topic
  11. Audio Signal Classification881 topic
  12. Music Information Retrieval881 topic
  13. Econophysics721 topic
  14. Multifractal Analysis721 topic
  15. Automatic481 topic
  16. Extraction481 topic
  17. Information Visualization371 topic
  18. Visual Analytics371 topic
  19. Continuous Queries241 topic
  20. Data Stream Management241 topic

Where does Eamonn Keogh work?

Eamonn Keogh's main affiliation in the publication record is University of California, Riverside, United States.

How many publications and citations does Eamonn Keogh have?

OpenAlex counts 404 works and 45,462 citations for Eamonn Keogh, an h-index of 98, ranking #9,582 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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