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Researcher · Institut national de recherche en sciences et technologies du numérique · France

Mickaël Binois

Mickaël Binois publishes mostly in Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research, on topics such as Advanced Multi-Objective Optimization Algorithms, Gaussian Processes and Bayesian Inference and Probabilistic and Robust Engineering Design.

ORCID 0000-0002-7225-1680 OpenAlex
World rank
#1,358,237
of 7,710,434 ranked researchers
Rank in France
#61,662
of 324,115
Works
84
Citations
1k
Citations per work
12.1
h-index
14
i10-index 22Top 25% in Artificial Intelligence
Mickaël Binois

What does Mickaël Binois research?

Mickaël Binois's work is mostly in Computer Science (44%), Decision Sciences (20%), Engineering (11%).

Physical Sciences: 45 works · 54.1% of their workComputer Science: 37 works · 43.5% of their workArtificial Intelligence: 21 works · 25.1% of their workComputational Theory and Mathematics: 15 works · 18.4% of their workEngineering: 9 works · 10.6% of their workControl and Systems Engineering: 5 works · 5.8% of their workAerospace Engineering: 4 works · 4.8% of their workEverything else: 22 works · 26.1% of their workSocial Sciences: 17 works · 19.8% of their workDecision Sciences: 17 works · 19.8% of their workManagement Science and Operations Research: 12 works · 14.5% of their workStatistics, Probability and Uncertainty: 4 works · 5.3% of their workTHEIR WORKMickaël Binois84works
Physical Sciences54%Social Sciences20%

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 Science3743.5%
    2. Engineering910.6%
  2. Everything else2226.1%
    1. Decision Sciences1719.8%
  1. 1Artificial Intelligence25% of their works
  2. 2Computational Theory and Mathematics18% of their works
  3. 3Management Science and Operations Research14% of their works
  4. 4Control and Systems Engineering6% of their works
  5. 5Statistics, Probability and Uncertainty5% of their works
  6. 6Aerospace Engineering5% of their works

Research topics

Which keywords describe Mickaël Binois's research?

The keywords of their largest research topics: Bayesian Optimization, Evolutionary Algorithms, Particle Swarm Optimization, Multiobjective Optimization, Surrogate Modeling, Gaussian Processes, Machine Learning and Sensitivity Analysis.

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 19 words, with their numbers
  1. Bayesian Optimization482 topics
  2. Evolutionary Algorithms432 topics
  3. Particle Swarm Optimization432 topics
  4. Multiobjective Optimization381 topic
  5. Surrogate Modeling381 topic
  6. Gaussian Processes311 topic
  7. Machine Learning311 topic
  8. Sensitivity Analysis111 topic
  9. Uncertainty Quantification111 topic
  10. Bandit Optimization101 topic
  11. Contextual Bandits101 topic
  12. Simulation Optimization91 topic
  13. Verification and Validation91 topic
  14. Experimental Design71 topic
  15. Optimization71 topic
  16. COVID-1961 topic
  17. Modeling61 topic
  18. Ant Colony Optimization51 topic
  19. Differential Evolution51 topic

Where does Mickaël Binois work?

Mickaël Binois's main affiliation in the publication record is Institut national de recherche en sciences et technologies du numérique, France.

How many publications and citations does Mickaël Binois have?

OpenAlex counts 84 works and 1,014 citations for Mickaël Binois, an h-index of 14, ranking #1,358,237 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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