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Researcher · University of Aberdeen · United Kingdom

Jaime Sevilla

Jaime Sevilla publishes mostly in Artificial Intelligence, Nuclear and High Energy Physics and Management Science and Operations Research, on topics such as Explainable Artificial Intelligence (XAI), Topic Modeling and Adversarial Robustness in Machine Learning.

ORCID 0000-0002-4454-1146 OpenAlex
World rank
#3,486,421
of 7,710,434 ranked researchers
Rank in United Kingdom
#230,270
of 367,258
Works
24
Citations
554
Citations per work
23.1
h-index
9
i10-index 8Top 49% in Artificial Intelligence
Jaime Sevilla

What does Jaime Sevilla research?

Jaime Sevilla's work is mostly in Computer Science (47%), Agricultural and Biological Sciences (8%), Physics and Astronomy (7%).

Physical Sciences: 13 works · 53.4% of their workComputer Science: 11 works · 46.7% of their workArtificial Intelligence: 11 works · 46.7% of their workPhysics and Astronomy: 2 works · 6.7% of their workNuclear and High Energy Physics: 2 works · 6.7% of their workEverything else: 6 works · 26.6% of their workSocial Sciences: 3 works · 11.7% of their workDecision Sciences: 2 works · 6.7% of their workManagement Science and Operations Research: 2 works · 6.7% of their workSocial Sciences: 1 works · 5.0% of their workSafety Research: 1 works · 5.0% of their workLife Sciences: 2 works · 8.3% of their workAgricultural and Biological Sciences: 2 works · 8.3% of their workFood Science: 1 works · 5.0% of their workGeneral Agricultural and Biological Sciences: 1 works · 3.3% of their workTHEIR WORKJaime Sevilla24works
Life Sciences8%Physical Sciences53%Social Sciences12%

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 Science1146.7%
    2. Physics and Astronomy26.7%
  2. Everything else626.6%
    1. Decision Sciences26.7%
    2. Social Sciences15.0%
    1. Agricultural and Biological Sciences28.3%
  1. 1Artificial Intelligence47% of their works
  2. 2Nuclear and High Energy Physics7% of their works
  3. 3Management Science and Operations Research7% of their works
  4. 4Food Science5% of their works
  5. 5Safety Research5% of their works
  6. 6General Agricultural and Biological Sciences3% of their works

Research topics

Which keywords describe Jaime Sevilla's research?

The keywords of their largest research topics: Machine Learning, Neural Networks, Big Data, Interpretable Models, Machine Learning Interpretability, Adversarial Examples, Deep Learning and Ethics.

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.

All 19 words, with their numbers
  1. Machine Learning114 topics
  2. Neural Networks93 topics
  3. Big Data52 topics
  4. Interpretable Models51 topic
  5. Machine Learning Interpretability51 topic
  6. Adversarial Examples31 topic
  7. Deep Learning31 topic
  8. Ethics31 topic
  9. Fairness31 topic
  10. Forecasting31 topic
  11. Machine Translation31 topic
  12. Time Series31 topic
  13. Word Representation31 topic
  14. Agroecology21 topic
  15. Food Sovereignty21 topic
  16. Food Waste21 topic
  17. R language21 topic
  18. Statistical Analysis21 topic
  19. Supply Chain21 topic

Where does Jaime Sevilla work?

Jaime Sevilla's main affiliation in the publication record is University of Aberdeen, United Kingdom.

How many publications and citations does Jaime Sevilla have?

OpenAlex counts 24 works and 554 citations for Jaime Sevilla, an h-index of 9, ranking #3,486,421 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised 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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