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Researcher · Jožef Stefan International Postgraduate School · Slovenia

Patrik Zajec

Patrik Zajec publishes mostly in Artificial Intelligence, Industrial and Manufacturing Engineering and Management Science and Operations Research, on topics such as Industrial Vision Systems and Defect Detection, Explainable Artificial Intelligence (XAI) and Big Data and Business Intelligence.

ORCID 0000-0002-6630-3106 OpenAlex
World rank
#1,804,873
of 7,710,434 ranked researchers
Rank in Slovenia
#1,411
of 9,404
Works
32
Citations
540
Citations per work
16.9
h-index
9
i10-index 9Top 49% in Artificial Intelligence
Patrik Zajec

What does Patrik Zajec research?

Patrik Zajec's work is mostly in Computer Science (44%), Engineering (18%), Decision Sciences (16%).

Physical Sciences: 20 works · 62.9% of their workComputer Science: 14 works · 44.4% of their workArtificial Intelligence: 12 works · 37.0% of their workComputer Vision and Pattern Recognition: 2 works · 7.4% of their workEngineering: 6 works · 18.5% of their workIndustrial and Manufacturing Engineering: 6 works · 18.5% of their workSocial Sciences: 8 works · 23.5% of their workDecision Sciences: 5 works · 16.1% of their workManagement Science and Operations Research: 3 works · 9.9% of their workStatistics, Probability and Uncertainty: 2 works · 6.2% of their workBusiness, Management and Accounting: 2 works · 7.4% of their workManagement Information Systems: 2 works · 7.4% of their workEverything else: 4 works · 13.6% of their workTHEIR WORKPatrik Zajec32works
Physical Sciences63%Social Sciences24%

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 Science1444.4%
    2. Engineering618.5%
    1. Decision Sciences516.1%
    2. Business, Management and Accounting27.4%
  3. Everything else413.6%
  1. 1Artificial Intelligence37% of their works
  2. 2Industrial and Manufacturing Engineering18% of their works
  3. 3Management Science and Operations Research10% of their works
  4. 4Computer Vision and Pattern Recognition7% of their works
  5. 5Management Information Systems7% of their works
  6. 6Statistics, Probability and Uncertainty6% of their works

Research topics

Which keywords describe Patrik Zajec's research?

The keywords of their largest research topics: Deep Learning, Fabric Defect Detection, Machine Vision, Big Data, Machine Learning, Supply Chain Management, Interpretable Models and Machine Learning Interpretability.

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 20 words, with their numbers
  1. Deep Learning162 topics
  2. Fabric Defect Detection111 topic
  3. Machine Vision111 topic
  4. Big Data102 topics
  5. Machine Learning102 topics
  6. Supply Chain Management102 topics
  7. Interpretable Models81 topic
  8. Machine Learning Interpretability81 topic
  9. Analytics61 topic
  10. Business Intelligence61 topic
  11. Active Learning51 topic
  12. Forecasting51 topic
  13. Healthcare Improvement51 topic
  14. Hough Transform51 topic
  15. Line Detection51 topic
  16. Semi-Supervised Learning51 topic
  17. Statistical Process Control51 topic
  18. Time Series51 topic
  19. Digital Twin41 topic
  20. Smart Manufacturing41 topic

Where does Patrik Zajec work?

Patrik Zajec's main affiliation in the publication record is Jožef Stefan International Postgraduate School, Slovenia.

How many publications and citations does Patrik Zajec have?

OpenAlex counts 32 works and 540 citations for Patrik Zajec, an h-index of 9, ranking #1,804,873 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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