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Researcher · Worcester Polytechnic Institute · United States

Xiangnan Kong

Xiangnan Kong publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology, on topics such as Advanced Graph Neural Networks, Complex Network Analysis Techniques and Text and Document Classification Technologies.

ORCID 0000-0002-7403-5869 OpenAlex
World rank
#463,826
of 7,710,434 ranked researchers
Rank in United States
#162,564
of 1,627,098
Works
202
Citations
5.7k
Citations per work
28.1
h-index
39
i10-index 98Top 2.3% in Artificial Intelligence
Xiangnan Kong

What does Xiangnan Kong research?

Xiangnan Kong's work is mostly in Computer Science (45%), Biochemistry, Genetics and Molecular Biology (9%), Physics and Astronomy (8%).

Physical Sciences: 109 works · 53.8% of their workComputer Science: 92 works · 45.4% of their workArtificial Intelligence: 63 works · 31.2% of their workComputer Vision and Pattern Recognition: 19 works · 9.4% of their workInformation Systems: 10 works · 4.8% of their workPhysics and Astronomy: 17 works · 8.4% of their workStatistical and Nonlinear Physics: 17 works · 8.4% of their workEverything else: 66 works · 32.5% of their workLife Sciences: 28 works · 13.7% of their workBiochemistry, Genetics and Molecular Biology: 17 works · 8.6% of their workMolecular Biology: 17 works · 8.6% of their workNeuroscience: 10 works · 5.1% of their workCognitive Neuroscience: 10 works · 5.1% of their workTHEIR WORKXiangnan Kong202works
Life Sciences14%Physical Sciences54%

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 Science9245.4%
    2. Physics and Astronomy178.4%
  2. Everything else6632.5%
    1. Biochemistry, Genetics and Molecular Biology178.6%
    2. Neuroscience105.1%
  1. 1Artificial Intelligence31% of their works
  2. 2Computer Vision and Pattern Recognition9% of their works
  3. 3Molecular Biology9% of their works
  4. 4Statistical and Nonlinear Physics8% of their works
  5. 5Cognitive Neuroscience5% of their works
  6. 6Information Systems5% of their works

Research topics

Which keywords describe Xiangnan Kong's research?

The keywords of their largest research topics: Representation Learning, Semi-Supervised Learning, Information Retrieval, Text Classification, Graph Neural Networks, Knowledge Graph Embedding, Community Structure and Network Dynamics.

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. Representation Learning542 topics
  2. Semi-Supervised Learning542 topics
  3. Information Retrieval482 topics
  4. Text Classification482 topics
  5. Graph Neural Networks441 topic
  6. Knowledge Graph Embedding441 topic
  7. Community Structure431 topic
  8. Network Dynamics431 topic
  9. Feature Selection261 topic
  10. Multi-label Learning261 topic
  11. Neural Networks221 topic
  12. Word Representation221 topic
  13. Functional Connectivity161 topic
  14. Resting-State fMRI161 topic
  15. Domain Adaptation101 topic
  16. Graph Matching101 topic
  17. Graph Processing101 topic
  18. Phishing101 topic
  19. Spam Detection101 topic
  20. Transfer Learning101 topic

Where does Xiangnan Kong work?

Xiangnan Kong's main affiliation in the publication record is Worcester Polytechnic Institute, United States.

How many publications and citations does Xiangnan Kong have?

OpenAlex counts 202 works and 5,678 citations for Xiangnan Kong, an h-index of 39, ranking #463,826 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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