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Researcher · University of Maryland, College Park · United States

Chenglei Si

Chenglei Si publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Health Informatics, on topics such as Topic Modeling, Natural Language Processing Techniques and Adversarial Robustness in Machine Learning.

OpenAlex
World rank
#2,188,211
of 7,710,434 ranked researchers
Rank in United States
#657,010
of 1,627,098
Works
33
Citations
1.4k
Citations per work
41.1
h-index
14
i10-index 17Top 25% in Artificial Intelligence
Chenglei Si

What does Chenglei Si research?

Chenglei Si's work is mostly in Computer Science (89%), Medicine (3%), Social Sciences (2%).

Physical Sciences: 29 works · 89.1% of their workComputer Science: 29 works · 89.1% of their workArtificial Intelligence: 27 works · 81.5% of their workComputer Vision and Pattern Recognition: 2 works · 6.5% of their workInformation Systems: 0 works · 1.1% of their workEverything else: 1 works · 4.3% of their workHealth Sciences: 1 works · 3.3% of their workMedicine: 1 works · 3.3% of their workHealth Informatics: 1 works · 3.3% of their workSocial Sciences: 1 works · 2.2% of their workSocial Sciences: 1 works · 2.2% of their workSociology and Political Science: 1 works · 2.2% of their workLife Sciences: 0 works · 1.1% of their workBiochemistry, Genetics and Molecular Biology: 0 works · 1.1% of their workMolecular Biology: 0 works · 1.1% of their workTHEIR WORKChenglei Si33works
Life Sciences1%Physical Sciences89%Health Sciences3%Social Sciences2%

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 Science2989.1%
  2. Everything else14.3%
    1. Medicine13.3%
    1. Social Sciences12.2%
    1. Biochemistry, Genetics and Molecular Biology01.1%
  1. 1Artificial Intelligence82% of their works
  2. 2Computer Vision and Pattern Recognition6% of their works
  3. 3Health Informatics3% of their works
  4. 4Sociology and Political Science2% of their works
  5. 5Molecular Biology1% of their works
  6. 6Information Systems1% of their works

Research topics

Which keywords describe Chenglei Si's research?

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

All 20 words, with their numbers
  1. Neural Networks413 topics
  2. Machine Translation301 topic
  3. Word Representation301 topic
  4. Neural Machine Translation231 topic
  5. Statistical Machine Translation231 topic
  6. Deep Learning133 topics
  7. Machine Learning92 topics
  8. Deep Neural Networks72 topics
  9. Adversarial Examples61 topic
  10. Robustness61 topic
  11. Image Captioning51 topic
  12. Visual Question Answering51 topic
  13. Interpretable Models41 topic
  14. Machine Learning Interpretability41 topic
  15. Acoustic Modeling31 topic
  16. Artificial Intelligence31 topic
  17. Healthcare31 topic
  18. Speaker Verification31 topic
  19. Graph Neural Networks21 topic
  20. Knowledge Graph Embedding21 topic

Where does Chenglei Si work?

Chenglei Si's main affiliation in the publication record is University of Maryland, College Park, United States.

How many publications and citations does Chenglei Si have?

OpenAlex counts 33 works and 1,355 citations for Chenglei Si, an h-index of 14, ranking #2,188,211 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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