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Researcher · AWS-Institute for Digitized Products and Processes · Germany

Marcel Mutz

Marcel Mutz publishes mostly in Information Systems, Civil and Structural Engineering and Water Science and Technology, on topics such as Water Quality Monitoring Technologies, Machine Learning in Materials Science and Semantic Web and Ontologies.

ORCID 0000-0002-5918-6407 OpenAlex
World rank
#5,372,122
of 7,710,434 ranked researchers
Rank in Germany
#277,764
of 364,343
Works
17
Citations
74
Citations per work
4.4
h-index
6
i10-index 2Top 46% in Information Systems
Marcel Mutz

What does Marcel Mutz research?

Marcel Mutz's work is mostly in Engineering (18%), Computer Science (12%), Environmental Science (8%).

Everything else: 8 works · 46.9% of their workPhysical Sciences: 8 works · 44.9% of their workEngineering: 3 works · 18.4% of their workCivil and Structural Engineering: 2 works · 10.2% of their workIndustrial and Manufacturing Engineering: 1 works · 8.2% of their workComputer Science: 2 works · 12.2% of their workInformation Systems: 2 works · 12.2% of their workEnvironmental Science: 1 works · 8.2% of their workWater Science and Technology: 1 works · 8.2% of their workMaterials Science: 1 works · 6.1% of their workMaterials Chemistry: 1 works · 6.1% of their workSocial Sciences: 1 works · 8.2% of their workDecision Sciences: 1 works · 8.2% of their workManagement Science and Operations Research: 1 works · 8.2% of their workTHEIR WORKMarcel Mutz17works
Physical Sciences45%Social Sciences8%

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. Everything else846.9%
    1. Engineering318.4%
    2. Computer Science212.2%
    3. Environmental Science18.2%
    4. Materials Science16.1%
    1. Decision Sciences18.2%
  1. 1Information Systems12% of their works
  2. 2Civil and Structural Engineering10% of their works
  3. 3Water Science and Technology8% of their works
  4. 4Industrial and Manufacturing Engineering8% of their works
  5. 5Management Science and Operations Research8% of their works
  6. 6Materials Chemistry6% of their works

Research topics

Which keywords describe Marcel Mutz's research?

The keywords of their largest research topics: Machine Learning, Aquaculture, Deep Learning, Water Quality Monitoring, High-Throughput, Materials Informatics, Big Data and Conservation Challenges.

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. Machine Learning52 topics
  2. Aquaculture41 topic
  3. Deep Learning42 topics
  4. Water Quality Monitoring41 topic
  5. High-Throughput31 topic
  6. Materials Informatics31 topic
  7. Big Data21 topic
  8. Conservation Challenges21 topic
  9. Crack Detection21 topic
  10. Data Analysis21 topic
  11. Fabric Defect Detection21 topic
  12. Freshwater Biodiversity21 topic
  13. Machine Vision21 topic
  14. Ontology21 topic
  15. Pavement21 topic
  16. QoS-Aware Middleware21 topic
  17. Semantic Web21 topic
  18. Semantic Web Services21 topic

Where does Marcel Mutz work?

Marcel Mutz's main affiliation in the publication record is AWS-Institute for Digitized Products and Processes, Germany.

How many publications and citations does Marcel Mutz have?

OpenAlex counts 17 works and 74 citations for Marcel Mutz, an h-index of 6, ranking #5,372,122 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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