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Researcher · Codeplay (United Kingdom) · United Kingdom

Kumudha Narasimhan

Kumudha Narasimhan publishes mostly in Computer Networks and Communications, Hardware and Architecture and Electrical and Electronic Engineering, on topics such as Parallel Computing and Optimization Techniques, Advanced Data Storage Technologies and Advanced Neural Network Applications.

ORCID 0000-0002-1142-3039 OpenAlex
World rank
#6,983,988
of 7,710,434 ranked researchers
Rank in United Kingdom
#357,288
of 367,258
Works
18
Citations
87
Citations per work
4.8
h-index
6
i10-index 3Top 77% in Computer Networks and Communications
Kumudha Narasimhan

What does Kumudha Narasimhan research?

Kumudha Narasimhan's work is mostly in Computer Science (43%), Engineering (28%).

Physical Sciences: 13 works · 70.4% of their workComputer Science: 8 works · 42.6% of their workComputer Networks and Communications: 3 works · 18.5% of their workHardware and Architecture: 2 works · 13.0% of their workComputer Vision and Pattern Recognition: 2 works · 11.1% of their workEngineering: 5 works · 27.8% of their workElectrical and Electronic Engineering: 2 works · 11.1% of their workCivil and Structural Engineering: 2 works · 9.3% of their workMechanics of Materials: 1 works · 7.4% of their workEverything else: 5 works · 29.6% of their workTHEIR WORKKumudhaNarasimhan18works
Physical Sciences70%

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 Science842.6%
    2. Engineering527.8%
  2. Everything else529.6%
  1. 1Computer Networks and Communications18% of their works
  2. 2Hardware and Architecture13% of their works
  3. 3Electrical and Electronic Engineering11% of their works
  4. 4Computer Vision and Pattern Recognition11% of their works
  5. 5Civil and Structural Engineering9% of their works
  6. 6Mechanics of Materials7% of their works

Research topics

Which keywords describe Kumudha Narasimhan's research?

The keywords of their largest research topics: Parallel Computing, High-Performance Computing, GPU Computing, Performance Optimization, Distributed Systems, Resource Management, Convolutional Neural Networks and Deep Learning.

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 22 words, with their numbers
  1. Parallel Computing122 topics
  2. High-Performance Computing112 topics
  3. GPU Computing71 topic
  4. Performance Optimization71 topic
  5. Distributed Systems62 topics
  6. Resource Management62 topics
  7. Convolutional Neural Networks51 topic
  8. Deep Learning51 topic
  9. Distributed Storage51 topic
  10. Mechanical Properties52 topics
  11. Network Coding51 topic
  12. Vibration Analysis52 topics
  13. Grid Computing41 topic
  14. Task Scheduling41 topic
  15. Finite Element Method31 topic
  16. Functionally Graded Materials31 topic
  17. Axially Moving Systems21 topic
  18. Big Data21 topic
  19. Cloud Computing21 topic
  20. Form-Finding21 topic
  21. Nonlinear Dynamics21 topic
  22. Tensegrity21 topic

Where does Kumudha Narasimhan work?

Kumudha Narasimhan's main affiliation in the publication record is Codeplay (United Kingdom), United Kingdom.

How many publications and citations does Kumudha Narasimhan have?

OpenAlex counts 18 works and 87 citations for Kumudha Narasimhan, an h-index of 6, ranking #6,983,988 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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