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Researcher · Massachusetts Institute of Technology · United States

Noga Zaslavsky

Noga Zaslavsky publishes mostly in Artificial Intelligence, Experimental and Cognitive Psychology and Cultural Studies, on topics such as Categorization, perception, and language, Language and cultural evolution and Natural Language Processing Techniques.

ORCID 0000-0003-3941-3518 OpenAlex
World rank
#2,264,926
of 7,710,434 ranked researchers
Rank in United States
#677,109
of 1,627,098
Works
54
Citations
964
Citations per work
17.9
h-index
13
i10-index 17Top 28% in Artificial Intelligence
Noga Zaslavsky

What does Noga Zaslavsky research?

Noga Zaslavsky's work is mostly in Computer Science (39%), Psychology (21%), Social Sciences (12%).

Physical Sciences: 21 works · 38.9% of their workComputer Science: 21 works · 38.9% of their workArtificial Intelligence: 18 works · 33.6% of their workComputer Vision and Pattern Recognition: 3 works · 5.3% of their workSocial Sciences: 19 works · 35.9% of their workPsychology: 11 works · 20.6% of their workExperimental and Cognitive Psychology: 11 works · 20.6% of their workSocial Sciences: 6 works · 11.5% of their workCultural Studies: 6 works · 11.5% of their workArts and Humanities: 2 works · 3.8% of their workLanguage and Linguistics: 2 works · 3.8% of their workEverything else: 9 works · 16.0% of their workLife Sciences: 5 works · 9.2% of their workNeuroscience: 5 works · 9.2% of their workCognitive Neuroscience: 5 works · 9.2% of their workTHEIR WORKNoga Zaslavsky54works
Life Sciences9%Physical Sciences39%Social Sciences36%

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 Science2138.9%
    1. Psychology1120.6%
    2. Social Sciences611.5%
    3. Arts and Humanities23.8%
  3. Everything else916.0%
    1. Neuroscience59.2%
  1. 1Artificial Intelligence34% of their works
  2. 2Experimental and Cognitive Psychology21% of their works
  3. 3Cultural Studies12% of their works
  4. 4Cognitive Neuroscience9% of their works
  5. 5Computer Vision and Pattern Recognition5% of their works
  6. 6Language and Linguistics4% of their works

Research topics

Which keywords describe Noga Zaslavsky's research?

The keywords of their largest research topics: Language, Cognition, Color Perception, Cultural Evolution, Social Learning, Spatial Reasoning, Neural Networks and Neural Machine Translation.

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. Language373 topics
  2. Cognition222 topics
  3. Color Perception151 topic
  4. Cultural Evolution151 topic
  5. Social Learning151 topic
  6. Spatial Reasoning151 topic
  7. Neural Networks132 topics
  8. Neural Machine Translation111 topic
  9. Statistical Machine Translation111 topic
  10. Machine Translation71 topic
  11. Metaphor71 topic
  12. Time71 topic
  13. Word Representation71 topic
  14. Backpropagation Learning61 topic
  15. Self-Organizing Maps61 topic
  16. Crossmodal Processing51 topic
  17. Markov Decision Processes51 topic
  18. Multisensory Integration51 topic
  19. Spoken Dialogue Systems51 topic

Where does Noga Zaslavsky work?

Noga Zaslavsky's main affiliation in the publication record is Massachusetts Institute of Technology, United States.

How many publications and citations does Noga Zaslavsky have?

OpenAlex counts 54 works and 964 citations for Noga Zaslavsky, an h-index of 13, ranking #2,264,926 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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