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Researcher · Akamai (United States) · United States

Malaikannan Sankarasubbu

Malaikannan Sankarasubbu publishes mostly in Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition, on topics such as Topic Modeling, Natural Language Processing Techniques and Machine Learning in Healthcare.

ORCID 0000-0002-7160-5133 OpenAlex
World rank
#1,523,423
of 7,710,434 ranked researchers
Rank in United States
#476,576
of 1,627,098
Works
27
Citations
811
Citations per work
30.0
h-index
11
i10-index 13Top 37% in Artificial Intelligence
Malaikannan Sankarasubbu

What does Malaikannan Sankarasubbu research?

Malaikannan Sankarasubbu's work is mostly in Computer Science (60%), Medicine (7%), Biochemistry, Genetics and Molecular Biology (6%).

Physical Sciences: 17 works · 64.0% of their workComputer Science: 16 works · 59.8% of their workArtificial Intelligence: 15 works · 54.2% of their workComputer Vision and Pattern Recognition: 2 works · 5.6% of their workPhysics and Astronomy: 1 works · 4.2% of their workStatistical and Nonlinear Physics: 1 works · 4.2% of their workEverything else: 6 works · 23.4% of their workHealth Sciences: 2 works · 7.0% of their workMedicine: 2 works · 7.0% of their workPulmonary and Respiratory Medicine: 1 works · 4.2% of their workRadiology, Nuclear Medicine and Imaging: 1 works · 2.8% of their workLife Sciences: 2 works · 5.6% of their workBiochemistry, Genetics and Molecular Biology: 2 works · 5.6% of their workMolecular Biology: 2 works · 5.6% of their workTHEIR WORKMalaikannanSankarasubbu27works
Life Sciences6%Physical Sciences64%Health 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 Science1659.8%
    2. Physics and Astronomy14.2%
  2. Everything else623.4%
    1. Medicine27.0%
    1. Biochemistry, Genetics and Molecular Biology25.6%
  1. 1Artificial Intelligence54% of their works
  2. 2Molecular Biology6% of their works
  3. 3Computer Vision and Pattern Recognition6% of their works
  4. 4Statistical and Nonlinear Physics4% of their works
  5. 5Pulmonary and Respiratory Medicine4% of their works
  6. 6Radiology, Nuclear Medicine and Imaging3% of their works

Research topics

Which keywords describe Malaikannan Sankarasubbu's research?

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

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. Neural Networks172 topics
  2. Machine Translation141 topic
  3. Word Representation141 topic
  4. Deep Learning124 topics
  5. Neural Machine Translation71 topic
  6. Statistical Machine Translation71 topic
  7. Machine Learning52 topics
  8. Electronic Health Records41 topic
  9. Healthcare41 topic
  10. Text Mining42 topics
  11. Image Captioning31 topic
  12. Model Reduction31 topic
  13. Partial Differential Equations31 topic
  14. Visual Question Answering31 topic
  15. Biomedical Literature21 topic
  16. Biomedical Ontologies21 topic
  17. Domain Adaptation21 topic
  18. Opinion Mining21 topic
  19. Sentiment Analysis21 topic
  20. Transfer Learning21 topic

Where does Malaikannan Sankarasubbu work?

Malaikannan Sankarasubbu's main affiliation in the publication record is Akamai (United States), United States.

How many publications and citations does Malaikannan Sankarasubbu have?

OpenAlex counts 27 works and 811 citations for Malaikannan Sankarasubbu, an h-index of 11, ranking #1,523,423 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.

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