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Researcher · DePaul University · United States

Robin Burke

Robin Burke publishes mostly in Information Systems, Artificial Intelligence and Management Science and Operations Research, on topics such as Recommender Systems and Techniques, Advanced Bandit Algorithms Research and Ethics and Social Impacts of AI.

ORCID 0000-0001-5766-6434 OpenAlex
World rank
#34,049
of 7,710,434 ranked researchers
Rank in United States
#12,969
of 1,627,098
Works
259
Citations
16k
Citations per work
61.3
h-index
57
i10-index 142Top 0.1% in Information Systems
Robin Burke

What does Robin Burke research?

Robin Burke's work is mostly in Computer Science (59%), Decision Sciences (9%), Social Sciences (4%).

Physical Sciences: 152 works · 58.8% of their workComputer Science: 152 works · 58.8% of their workInformation Systems: 74 works · 28.6% of their workArtificial Intelligence: 54 works · 20.7% of their workComputer Vision and Pattern Recognition: 15 works · 5.9% of their workSignal Processing: 9 works · 3.6% of their workEverything else: 73 works · 28.0% of their workSocial Sciences: 34 works · 13.2% of their workDecision Sciences: 24 works · 9.3% of their workManagement Science and Operations Research: 24 works · 9.3% of their workSocial Sciences: 10 works · 3.9% of their workSafety Research: 10 works · 3.9% of their workTHEIR WORKRobin Burke259works
Physical Sciences59%Social Sciences13%

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 Science15258.8%
  2. Everything else7328.0%
    1. Decision Sciences249.3%
    2. Social Sciences103.9%
  1. 1Information Systems29% of their works
  2. 2Artificial Intelligence21% of their works
  3. 3Management Science and Operations Research9% of their works
  4. 4Computer Vision and Pattern Recognition6% of their works
  5. 5Safety Research4% of their works
  6. 6Signal Processing4% of their works

Research topics

Which keywords describe Robin Burke's research?

The keywords of their largest research topics: Neural Networks, Deep Learning, Collaborative Filtering, Matrix Factorization, Bandit Optimization, Bayesian Optimization, Ethics and Fairness.

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.

All 18 words, with their numbers
  1. Neural Networks1762 topics
  2. Deep Learning1712 topics
  3. Collaborative Filtering1511 topic
  4. Matrix Factorization1511 topic
  5. Bandit Optimization601 topic
  6. Bayesian Optimization601 topic
  7. Ethics271 topic
  8. Fairness271 topic
  9. Machine Translation251 topic
  10. Word Representation251 topic
  11. Crowdsourcing201 topic
  12. Graph Neural Networks201 topic
  13. Knowledge Graph Embedding201 topic
  14. Mechanical Turk201 topic
  15. Ontology201 topic
  16. Semantic Web201 topic
  17. GPS Trajectories191 topic
  18. Trajectory Data Mining191 topic

Where does Robin Burke work?

Robin Burke's main affiliation in the publication record is DePaul University, United States.

How many publications and citations does Robin Burke have?

OpenAlex counts 259 works and 15,885 citations for Robin Burke, an h-index of 57, ranking #34,049 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised 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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