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Researcher · Amazon (United States) · United States

Anjali Narayan-Chen

Anjali Narayan-Chen publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, on topics such as Topic Modeling, Natural Language Processing Techniques and Speech and dialogue systems.

OpenAlex
World rank
#3,371,618
of 7,710,434 ranked researchers
Rank in United States
#949,521
of 1,627,098
Works
21
Citations
228
Citations per work
10.9
h-index
7
i10-index 4Top 65% in Artificial Intelligence
Anjali Narayan-Chen

What does Anjali Narayan-Chen research?

Anjali Narayan-Chen's work is mostly in Computer Science (76%), Engineering (4%), Arts and Humanities (4%).

Physical Sciences: 17 works · 80.0% of their workComputer Science: 16 works · 76.4% of their workArtificial Intelligence: 12 works · 56.4% of their workComputer Vision and Pattern Recognition: 3 works · 14.5% of their workSignal Processing: 1 works · 5.5% of their workEngineering: 1 works · 3.6% of their workBuilding and Construction: 1 works · 3.6% of their workEverything else: 3 works · 12.8% of their workSocial Sciences: 2 works · 7.2% of their workArts and Humanities: 1 works · 3.6% of their workVisual Arts and Performing Arts: 1 works · 3.6% of their workPsychology: 1 works · 3.6% of their workSocial Psychology: 1 works · 3.6% of their workTHEIR WORKAnjaliNarayan-Chen21works
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 Science1676.4%
    2. Engineering13.6%
  2. Everything else312.8%
    1. Arts and Humanities13.6%
    2. Psychology13.6%
  1. 1Artificial Intelligence56% of their works
  2. 2Computer Vision and Pattern Recognition14% of their works
  3. 3Signal Processing6% of their works
  4. 4Visual Arts and Performing Arts4% of their works
  5. 5Building and Construction4% of their works
  6. 6Social Psychology4% of their works

Research topics

Which keywords describe Anjali Narayan-Chen's research?

The keywords of their largest research topics: Neural Networks, Machine Translation, Word Representation, Neural Machine Translation, Statistical Machine Translation, Deep Learning, Image Captioning and Markov Decision Processes.

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 18 words, with their numbers
  1. Neural Networks172 topics
  2. Machine Translation121 topic
  3. Word Representation121 topic
  4. Neural Machine Translation91 topic
  5. Statistical Machine Translation91 topic
  6. Deep Learning82 topics
  7. Image Captioning51 topic
  8. Markov Decision Processes51 topic
  9. Spoken Dialogue Systems51 topic
  10. Visual Question Answering51 topic
  11. Audio Signal Classification31 topic
  12. Music Information Retrieval31 topic
  13. Comics21 topic
  14. Graphic Novels21 topic
  15. Humor Styles Questionnaire21 topic
  16. Interactive Evolutionary Computation21 topic
  17. Music Generation21 topic
  18. Psychological Well-being21 topic

Where does Anjali Narayan-Chen work?

Anjali Narayan-Chen's main affiliation in the publication record is Amazon (United States), United States.

How many publications and citations does Anjali Narayan-Chen have?

OpenAlex counts 21 works and 228 citations for Anjali Narayan-Chen, an h-index of 7, ranking #3,371,618 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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