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Researcher · University of Siena · Italy

Kamyar Zeinalipour

Kamyar Zeinalipour publishes mostly in Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics, on topics such as Natural Language Processing Techniques, Topic Modeling and Text Readability and Simplification.

ORCID 0009-0006-3014-2511 OpenAlex
World rank
#4,457,644
of 7,710,434 ranked researchers
Rank in Italy
#150,755
of 242,206
Works
37
Citations
29
Citations per work
0.8
h-index
3
i10-index 1Top 95% in Artificial Intelligence
Kamyar Zeinalipour

What does Kamyar Zeinalipour research?

Kamyar Zeinalipour's work is mostly in Computer Science (63%), Biochemistry, Genetics and Molecular Biology (8%), Psychology (6%).

Physical Sciences: 23 works · 62.5% of their workComputer Science: 23 works · 62.5% of their workArtificial Intelligence: 20 works · 53.4% of their workComputational Theory and Mathematics: 2 works · 5.7% of their workInformation Systems: 1 works · 3.4% of their workEverything else: 8 works · 21.5% of their workLife Sciences: 3 works · 8.0% of their workBiochemistry, Genetics and Molecular Biology: 3 works · 8.0% of their workMolecular Biology: 3 works · 8.0% of their workSocial Sciences: 3 works · 8.0% of their workPsychology: 2 works · 5.7% of their workDevelopmental and Educational Psychology: 2 works · 5.7% of their workArts and Humanities: 1 works · 2.3% of their workLanguage and Linguistics: 1 works · 2.3% of their workTHEIR WORKKamyarZeinalipour37works
Life Sciences8%Physical Sciences63%Social Sciences8%

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 Science2362.5%
  2. Everything else821.5%
    1. Biochemistry, Genetics and Molecular Biology38.0%
    1. Psychology25.7%
    2. Arts and Humanities12.3%
  1. 1Artificial Intelligence53% of their works
  2. 2Molecular Biology8% of their works
  3. 3Computational Theory and Mathematics6% of their works
  4. 4Developmental and Educational Psychology6% of their works
  5. 5Information Systems3% of their works
  6. 6Language and Linguistics2% of their works

Research topics

Which keywords describe Kamyar Zeinalipour's research?

The keywords of their largest research topics: Neural Machine Translation, Neural Networks, Statistical Machine Translation, Machine Learning, Machine Translation, Natural Language Processing, Word Representation and Readability Assessment.

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. Neural Machine Translation161 topic
  2. Neural Networks162 topics
  3. Statistical Machine Translation161 topic
  4. Machine Learning154 topics
  5. Machine Translation91 topic
  6. Natural Language Processing92 topics
  7. Word Representation91 topic
  8. Readability Assessment71 topic
  9. Text Simplification71 topic
  10. Molecular Docking31 topic
  11. Protein31 topic
  12. Subcellular Localization31 topic
  13. Virtual Screening31 topic
  14. Decision Support System21 topic
  15. Epitope Prediction21 topic
  16. Expert Systems21 topic
  17. Ontology21 topic
  18. Peptide-MHC Binding21 topic
  19. Semantic Web21 topic

Where does Kamyar Zeinalipour work?

Kamyar Zeinalipour's main affiliation in the publication record is University of Siena, Italy.

How many publications and citations does Kamyar Zeinalipour have?

OpenAlex counts 37 works and 29 citations for Kamyar Zeinalipour, an h-index of 3, ranking #4,457,644 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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