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Researcher · Microsoft (United States) · United States

Rich Caruana

Rich Caruana publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability, on topics such as Machine Learning and Data Classification, Explainable Artificial Intelligence (XAI) and Neural Networks and Applications.

ORCID 0000-0002-6383-7786 OpenAlex
World rank
#36,993
of 7,710,434 ranked researchers
Rank in United States
#14,153
of 1,627,098
Works
191
Citations
33k
Citations per work
170.3
h-index
58
i10-index 106Top 0.6% in Artificial Intelligence
Rich Caruana

What does Rich Caruana research?

Rich Caruana's work is mostly in Computer Science (69%), Mathematics (3%), Medicine (2%).

Physical Sciences: 136 works · 71.1% of their workComputer Science: 131 works · 68.6% of their workArtificial Intelligence: 111 works · 58.2% of their workComputer Vision and Pattern Recognition: 11 works · 5.8% of their workInformation Systems: 5 works · 2.5% of their workSignal Processing: 4 works · 2.1% of their workMathematics: 5 works · 2.5% of their workStatistics and Probability: 5 works · 2.5% of their workEverything else: 52 works · 27.2% of their workHealth Sciences: 3 works · 1.7% of their workMedicine: 3 works · 1.7% of their workObstetrics and Gynecology: 3 works · 1.7% of their workTHEIR WORKRich Caruana191works
Physical Sciences71%Health 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 Science13168.6%
    2. Mathematics52.5%
  2. Everything else5227.2%
    1. Medicine31.7%
  1. 1Artificial Intelligence58% of their works
  2. 2Computer Vision and Pattern Recognition6% of their works
  3. 3Statistics and Probability2% of their works
  4. 4Information Systems2% of their works
  5. 5Signal Processing2% of their works
  6. 6Obstetrics and Gynecology2% of their works

Research topics

Which keywords describe Rich Caruana's research?

The keywords of their largest research topics: Deep Neural Networks, Deep Learning, Classification, Neural Networks, Hyperparameter Optimization, Noisy Labels, Interpretable Models and Machine Learning Interpretability.

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 21 words, with their numbers
  1. Deep Neural Networks972 topics
  2. Deep Learning764 topics
  3. Classification652 topics
  4. Neural Networks553 topics
  5. Hyperparameter Optimization531 topic
  6. Noisy Labels531 topic
  7. Interpretable Models441 topic
  8. Machine Learning Interpretability441 topic
  9. Machine Learning362 topics
  10. Backpropagation Learning231 topic
  11. Self-Organizing Maps231 topic
  12. Active Learning201 topic
  13. Semi-Supervised Learning201 topic
  14. Electronic Health Records171 topic
  15. Healthcare171 topic
  16. Adversarial Examples161 topic
  17. Machine Translation161 topic
  18. Robustness161 topic
  19. Word Representation161 topic
  20. Imbalanced Data121 topic
  21. SMOTE121 topic

Where does Rich Caruana work?

Rich Caruana's main affiliation in the publication record is Microsoft (United States), United States.

How many publications and citations does Rich Caruana have?

OpenAlex counts 191 works and 32,532 citations for Rich Caruana, an h-index of 58, ranking #36,993 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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