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Researcher · Nvidia (United States) · United States

Sara Rabhi

Sara Rabhi publishes mostly in Artificial Intelligence, Information Systems and Molecular Biology, on topics such as Recommender Systems and Techniques, Topic Modeling and Machine Learning in Healthcare.

ORCID 0000-0003-4014-9152 OpenAlex
World rank
#4,299,160
of 7,710,434 ranked researchers
Rank in United States
#1,155,403
of 1,627,098
Works
18
Citations
313
Citations per work
17.4
h-index
7
i10-index 6Top 65% in Artificial Intelligence
Sara Rabhi

What does Sara Rabhi research?

Sara Rabhi's work is mostly in Computer Science (66%), Biochemistry, Genetics and Molecular Biology (6%), Decision Sciences (6%).

Physical Sciences: 12 works · 65.5% of their workComputer Science: 12 works · 65.5% of their workArtificial Intelligence: 7 works · 38.5% of their workInformation Systems: 4 works · 21.2% of their workComputer Vision and Pattern Recognition: 1 works · 5.8% of their workEverything else: 3 works · 19.1% of their workLife Sciences: 1 works · 5.8% of their workBiochemistry, Genetics and Molecular Biology: 1 works · 5.8% of their workMolecular Biology: 1 works · 5.8% of their workSocial Sciences: 1 works · 5.8% of their workDecision Sciences: 1 works · 5.8% of their workManagement Science and Operations Research: 1 works · 5.8% of their workHealth Sciences: 1 works · 3.8% of their workMedicine: 1 works · 3.8% of their workEndocrinology, Diabetes and Metabolism: 1 works · 3.8% of their workTHEIR WORKSara Rabhi18works
Life Sciences6%Physical Sciences66%Health Sciences4%Social Sciences6%

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 Science1265.5%
  2. Everything else319.1%
    1. Biochemistry, Genetics and Molecular Biology15.8%
    1. Decision Sciences15.8%
    1. Medicine13.8%
  1. 1Artificial Intelligence38% of their works
  2. 2Information Systems21% of their works
  3. 3Molecular Biology6% of their works
  4. 4Computer Vision and Pattern Recognition6% of their works
  5. 5Management Science and Operations Research6% of their works
  6. 6Endocrinology, Diabetes and Metabolism4% of their works

Research topics

Which keywords describe Sara Rabhi's research?

The keywords of their largest research topics: Deep Learning, Neural Networks, Collaborative Filtering, Matrix Factorization, Machine Translation, Word Representation, Hyperparameter Optimization 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 19 words, with their numbers
  1. Deep Learning184 topics
  2. Neural Networks172 topics
  3. Collaborative Filtering101 topic
  4. Matrix Factorization101 topic
  5. Machine Translation71 topic
  6. Word Representation71 topic
  7. Hyperparameter Optimization52 topics
  8. Electronic Health Records41 topic
  9. Healthcare41 topic
  10. Bandit Optimization31 topic
  11. Bayesian Optimization31 topic
  12. Diabetes21 topic
  13. Graph Neural Networks21 topic
  14. Hypoglycemia21 topic
  15. Instance Selection21 topic
  16. Knowledge Graph Embedding21 topic
  17. Noisy Labels21 topic
  18. Opinion Mining21 topic
  19. Sentiment Analysis21 topic

Where does Sara Rabhi work?

Sara Rabhi's main affiliation in the publication record is Nvidia (United States), United States.

How many publications and citations does Sara Rabhi have?

OpenAlex counts 18 works and 313 citations for Sara Rabhi, an h-index of 7, ranking #4,299,160 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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