Niusha Shafiabady
Niusha Shafiabady publishes mostly in Artificial Intelligence, Information Systems and Safety Research, on topics such as Neural Networks and Applications, Metaheuristic Optimization Algorithms Research and Fuzzy Logic and Control Systems.
- World rank
- #418,678 of 1,633,909 ranked researchers
- Rank in Australia
- #11,874 of 35,497
- Works
- 15
- Citations
- 73
- Citations per work
- 4.9
What does Niusha Shafiabady research?
Shares of their own output, by the field each of their topics belongs to. The grey slice is everything not listed.
- 1Artificial Intelligence50% of their works
- 2Information Systems33% of their works
- 3Safety Research17% of their works
Research topics
Which keywords describe Niusha Shafiabady's research?
The keywords of their largest research topics: E-Learning, Machine Learning, Blockchain, Differential Evolution, Education, Education Technology, Ethics and Fairness.
- Type-2 Fuzzy Sets
- Qualitative Data Analysis
- Neural Networks
- Fairness
- Education Technology
- Differential Evolution
- Machine Learning
- E-Learning
- Blockchain
- Education
- Ethics
- Fuzzy Logic Systems
- Particle Swarm Optimization
- Self-Organizing Maps
Size is their works in the topics tagged with each word, from their 6 largest topics. Each links to the topic it comes from most.
All 14 words, with their numbers
- E-Learning22 topics
- Machine Learning22 topics
- Blockchain11 topic
- Differential Evolution11 topic
- Education11 topic
- Education Technology11 topic
- Ethics11 topic
- Fairness11 topic
- Fuzzy Logic Systems11 topic
- Neural Networks11 topic
- Particle Swarm Optimization11 topic
- Qualitative Data Analysis11 topic
- Self-Organizing Maps11 topic
- Type-2 Fuzzy Sets11 topic
Where does Niusha Shafiabady work?
Niusha Shafiabady's main affiliation in the publication record is Charles Darwin University, Australia.
How many publications and citations does Niusha Shafiabady have?
Science Explorer counts 15 works and 73 citations for Niusha Shafiabady, ranking #418,678 of 1,633,909 researchers worldwide on the composite 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 are in the interactive view on the map. Is this your page? Request a correction or removal.