Science Explorer Back to mapMap
Discussion
Researcher · SINTEF · Norway

Mass Soldal Lund

Mass Soldal Lund publishes mostly in Information Systems, Artificial Intelligence and Software, on topics such as Information and Cyber Security, Risk and Safety Analysis and Software Engineering Techniques and Practices.

ORCID 0000-0002-5286-982X OpenAlex
World rank
#594,636
of 7,710,434 ranked researchers
Rank in Norway
#3,695
of 33,005
Works
70
Citations
1.4k
Citations per work
20.4
h-index
18
i10-index 25Top 5.7% in Information Systems
Mass Soldal Lund

What does Mass Soldal Lund research?

Mass Soldal Lund's work is mostly in Computer Science (53%), Decision Sciences (6%), Social Sciences (5%).

Physical Sciences: 37 works · 53.2% of their workComputer Science: 37 works · 53.2% of their workInformation Systems: 16 works · 23.1% of their workArtificial Intelligence: 8 works · 11.2% of their workSoftware: 8 works · 11.2% of their workComputer Networks and Communications: 5 works · 7.7% of their workEverything else: 25 works · 35.6% of their workSocial Sciences: 8 works · 11.2% of their workDecision Sciences: 5 works · 6.5% of their workStatistics, Probability and Uncertainty: 5 works · 6.5% of their workSocial Sciences: 3 works · 4.7% of their workSociology and Political Science: 3 works · 4.7% of their workTHEIR WORKMass Soldal Lund70works
Physical Sciences53%Social Sciences11%

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 Science3753.2%
  2. Everything else2535.6%
    1. Decision Sciences56.5%
    2. Social Sciences34.7%
  1. 1Information Systems23% of their works
  2. 2Artificial Intelligence11% of their works
  3. 3Software11% of their works
  4. 4Computer Networks and Communications8% of their works
  5. 5Statistics, Probability and Uncertainty6% of their works
  6. 6Sociology and Political Science5% of their works

Research topics

Which keywords describe Mass Soldal Lund's research?

The keywords of their largest research topics: Information Security, Policy Compliance, Requirements Engineering, Bayesian Networks, Fault Tree Analysis, Agile Software Development, Domain-Specific Languages and Empirical Studies.

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 17 words, with their numbers
  1. Information Security161 topic
  2. Policy Compliance161 topic
  3. Requirements Engineering162 topics
  4. Bayesian Networks101 topic
  5. Fault Tree Analysis101 topic
  6. Agile Software Development91 topic
  7. Domain-Specific Languages91 topic
  8. Empirical Studies91 topic
  9. Model-Driven Engineering91 topic
  10. Code Clone Detection81 topic
  11. Refactoring81 topic
  12. Architecture-Based Approach71 topic
  13. Autonomic Computing71 topic
  14. Self-Adaptive Systems71 topic
  15. Software Reliability Modeling71 topic
  16. Log Analysis61 topic
  17. Performance Prediction61 topic

Where does Mass Soldal Lund work?

Mass Soldal Lund's main affiliation in the publication record is SINTEF, Norway.

How many publications and citations does Mass Soldal Lund have?

OpenAlex counts 70 works and 1,430 citations for Mass Soldal Lund, an h-index of 18, ranking #594,636 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 Mass Soldal Lund. 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.