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Researcher · University of Massachusetts Amherst · United States

Philip S. Thomas

Philip S. Thomas publishes mostly in Artificial Intelligence, Management Science and Operations Research and Economics and Econometrics, on topics such as Reinforcement Learning in Robotics, Advanced Bandit Algorithms Research and Machine Learning and Algorithms.

ORCID 0000-0002-9904-1800 OpenAlex
World rank
#1,644,507
of 7,710,434 ranked researchers
Rank in United States
#510,232
of 1,627,098
Works
122
Citations
2.1k
Citations per work
17.1
h-index
22
i10-index 37Top 10% in Artificial Intelligence
Philip S. Thomas

What does Philip S. Thomas research?

Philip S. Thomas's work is mostly in Computer Science (37%), Decision Sciences (13%), Economics, Econometrics and Finance (5%).

Physical Sciences: 50 works · 40.7% of their workComputer Science: 45 works · 36.9% of their workArtificial Intelligence: 45 works · 36.9% of their workEngineering: 5 works · 3.8% of their workElectrical and Electronic Engineering: 5 works · 3.8% of their workEverything else: 43 works · 35.4% of their workSocial Sciences: 26 works · 21.0% of their workDecision Sciences: 15 works · 12.7% of their workManagement Science and Operations Research: 15 works · 12.7% of their workEconomics, Econometrics and Finance: 6 works · 5.1% of their workEconomics and Econometrics: 6 works · 5.1% of their workBusiness, Management and Accounting: 4 works · 3.2% of their workStrategy and Management: 4 works · 3.2% of their workLife Sciences: 4 works · 2.9% of their workNeuroscience: 4 works · 2.9% of their workCognitive Neuroscience: 4 works · 2.9% of their workTHEIR WORKPhilip S. Thomas122works
Life Sciences3%Physical Sciences41%Social Sciences21%

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 Science4536.9%
    2. Engineering53.8%
  2. Everything else4335.4%
    1. Decision Sciences1512.7%
    2. Economics, Econometrics and Finance65.1%
    3. Business, Management and Accounting43.2%
    1. Neuroscience42.9%
  1. 1Artificial Intelligence37% of their works
  2. 2Management Science and Operations Research13% of their works
  3. 3Economics and Econometrics5% of their works
  4. 4Electrical and Electronic Engineering4% of their works
  5. 5Strategy and Management3% of their works
  6. 6Cognitive Neuroscience3% of their works

Research topics

Which keywords describe Philip S. Thomas's research?

The keywords of their largest research topics: Deep Learning, Neural Networks, Reinforcement Learning, Robotics, Online Learning, Machine Learning, Bandit Optimization and Bayesian Optimization.

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 20 words, with their numbers
  1. Deep Learning674 topics
  2. Neural Networks634 topics
  3. Reinforcement Learning441 topic
  4. Robotics441 topic
  5. Online Learning322 topics
  6. Machine Learning273 topics
  7. Bandit Optimization251 topic
  8. Bayesian Optimization251 topic
  9. Active Learning101 topic
  10. Semi-Supervised Learning101 topic
  11. Classification91 topic
  12. Genetic Programming91 topic
  13. Adversarial Examples81 topic
  14. Robustness81 topic
  15. Concept Drift71 topic
  16. Data Streams71 topic
  17. Memristor61 topic
  18. Neuromorphic Computing61 topic
  19. Backpropagation Learning51 topic
  20. Self-Organizing Maps51 topic

Where does Philip S. Thomas work?

Philip S. Thomas's main affiliation in the publication record is University of Massachusetts Amherst, United States.

How many publications and citations does Philip S. Thomas have?

OpenAlex counts 122 works and 2,092 citations for Philip S. Thomas, an h-index of 22, ranking #1,644,507 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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