Science Explorer Back to mapMap
Discussion
Researcher · TU Dortmund University · Germany

Matthias G.R. Faes

Matthias G.R. Faes publishes mostly in Statistics, Probability and Uncertainty, Civil and Structural Engineering and Computational Theory and Mathematics, on topics such as Probabilistic and Robust Engineering Design, Structural Health Monitoring Techniques and Advanced Multi-Objective Optimization Algorithms.

ORCID 0000-0003-3341-3410 OpenAlex
World rank
#270,200
of 7,710,434 ranked researchers
Rank in Germany
#13,642
of 364,343
Works
213
Citations
2.9k
Citations per work
13.8
h-index
30
i10-index 81Top 7.2% in Statistics, Probability and Uncertainty
Matthias G.R. Faes

What does Matthias G.R. Faes research?

Matthias G.R. Faes's work is mostly in Engineering (36%), Decision Sciences (25%), Computer Science (6%).

Physical Sciences: 89 works · 41.9% of their workEngineering: 76 works · 35.6% of their workCivil and Structural Engineering: 38 works · 18.0% of their workControl and Systems Engineering: 13 works · 6.3% of their workMechanical Engineering: 13 works · 6.3% of their workMechanics of Materials: 11 works · 5.0% of their workComputer Science: 13 works · 6.3% of their workComputational Theory and Mathematics: 13 works · 6.3% of their workEverything else: 70 works · 32.8% of their workSocial Sciences: 54 works · 25.3% of their workDecision Sciences: 54 works · 25.3% of their workStatistics, Probability and Uncertainty: 54 works · 25.3% of their workTHEIR WORKMatthias G.R.Faes213works
Physical Sciences42%Social Sciences25%

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. Engineering7635.6%
    2. Computer Science136.3%
  2. Everything else7032.8%
    1. Decision Sciences5425.3%
  1. 1Statistics, Probability and Uncertainty25% of their works
  2. 2Civil and Structural Engineering18% of their works
  3. 3Computational Theory and Mathematics6% of their works
  4. 4Mechanical Engineering6% of their works
  5. 5Control and Systems Engineering6% of their works
  6. 6Mechanics of Materials5% of their works

Research topics

Which keywords describe Matthias G.R. Faes's research?

The keywords of their largest research topics: Sensitivity Analysis, Polynomial Chaos, Uncertainty Quantification, Vibration-based Damage Identification, Wireless Sensors, Evolutionary Algorithms, Multiobjective Optimization and Machine Learning.

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 18 words, with their numbers
  1. Sensitivity Analysis1512 topics
  2. Polynomial Chaos1381 topic
  3. Uncertainty Quantification1381 topic
  4. Vibration-based Damage Identification521 topic
  5. Wireless Sensors521 topic
  6. Evolutionary Algorithms351 topic
  7. Multiobjective Optimization351 topic
  8. Machine Learning322 topics
  9. Deep Learning191 topic
  10. Partial Differential Equations191 topic
  11. Assembly Planning161 topic
  12. Design for Manufacture161 topic
  13. Fatigue Crack Closure141 topic
  14. Fracture Toughness Testing141 topic
  15. Fault Detection131 topic
  16. Level Set Method131 topic
  17. Process Monitoring131 topic
  18. Structural Boundary Design131 topic

Where does Matthias G.R. Faes work?

Matthias G.R. Faes's main affiliation in the publication record is TU Dortmund University, Germany.

How many publications and citations does Matthias G.R. Faes have?

OpenAlex counts 213 works and 2,940 citations for Matthias G.R. Faes, an h-index of 30, ranking #270,200 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

Ask a question or share a note about Matthias G.R. Faes. Keep it to the research: no personal attacks, advertising or links. Any reader can report a post, which collapses it for everyone until it is opened.