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Researcher · Kenyon College · United States

Jon Chun

Jon Chun publishes mostly in Artificial Intelligence, Safety Research and Health Informatics, on topics such as Ethics and Social Impacts of AI, Explainable Artificial Intelligence (XAI) and Topic Modeling.

ORCID 0000-0002-5315-6784 OpenAlex
World rank
#2,602,575
of 7,710,434 ranked researchers
Rank in United States
#763,183
of 1,627,098
Works
36
Citations
358
Citations per work
9.9
h-index
8
i10-index 6Top 56% in Artificial Intelligence
Jon Chun

What does Jon Chun research?

Jon Chun's work is mostly in Computer Science (51%), Social Sciences (20%), Medicine (8%).

Physical Sciences: 18 works · 50.7% of their workComputer Science: 18 works · 50.7% of their workArtificial Intelligence: 18 works · 50.7% of their workSocial Sciences: 9 works · 25.9% of their workSocial Sciences: 7 works · 20.5% of their workSafety Research: 6 works · 17.8% of their workSociology and Political Science: 1 works · 2.7% of their workBusiness, Management and Accounting: 1 works · 2.7% of their workManagement of Technology and Innovation: 1 works · 2.7% of their workPsychology: 1 works · 2.7% of their workSocial Psychology: 1 works · 2.7% of their workEverything else: 5 works · 15.2% of their workHealth Sciences: 3 works · 8.2% of their workMedicine: 3 works · 8.2% of their workHealth Informatics: 3 works · 8.2% of their workTHEIR WORKJon Chun36works
Physical Sciences51%Health Sciences8%Social Sciences26%

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 Science1850.7%
    1. Social Sciences720.5%
    2. Business, Management and Accounting12.7%
    3. Psychology12.7%
  3. Everything else515.2%
    1. Medicine38.2%
  1. 1Artificial Intelligence51% of their works
  2. 2Safety Research18% of their works
  3. 3Health Informatics8% of their works
  4. 4Social Psychology3% of their works
  5. 5Sociology and Political Science3% of their works
  6. 6Management of Technology and Innovation3% of their works

Research topics

Which keywords describe Jon Chun's research?

The keywords of their largest research topics: Artificial Intelligence, Machine Learning, Big Data, Ethics, Fairness, Interpretable Models, Machine Learning Interpretability and Neural Networks.

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. Artificial Intelligence244 topics
  2. Machine Learning243 topics
  3. Big Data192 topics
  4. Ethics131 topic
  5. Fairness131 topic
  6. Interpretable Models121 topic
  7. Machine Learning Interpretability121 topic
  8. Neural Networks122 topics
  9. Machine Translation81 topic
  10. Word Representation81 topic
  11. Healthcare61 topic
  12. Medical Imaging61 topic
  13. Opinion Mining51 topic
  14. Sentiment Analysis51 topic
  15. Automatic41 topic
  16. Extraction41 topic
  17. Cyberbiosecurity31 topic
  18. Legal Implications31 topic
  19. Agent-Based Modeling21 topic
  20. Multi-Agent Systems21 topic

Where does Jon Chun work?

Jon Chun's main affiliation in the publication record is Kenyon College, United States.

How many publications and citations does Jon Chun have?

OpenAlex counts 36 works and 358 citations for Jon Chun, an h-index of 8, ranking #2,602,575 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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