Mikel Elkano: h-index, Total Citations, and Citation Map
Mikel Elkano's h-index is 9 (9 i10-index, 986+ total citations across 27+ publications) according to Google Scholar as of June 2026. Mikel Elkano is affiliated with Neuraptic AI.
Mikel Elkano is a researcher affiliated with Neuraptic AI, specializing in Machine Learning, Computational Neuroscience. Their work has been cited 986 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Mikel Elkano's Citation Metrics
Bibliometric impact based on 27 indexed publications.
- H-Index
- 9
- i10-Index
- 9
- Total Citations
- 986
- Citing Countries
- 38
As of June 2026.
Mikel Elkano has an h-index of 9 and 986 total citations across 27 publications, with research cited by institutions in 38 countries.
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Global Impact Map
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CC-integrals: Choquet-like copula-based aggregation functions and its application in fuzzy rule-based classification systems
2017200
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
4 citing papers could not be classified (no author data) — excluded from the percentages above.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Mikel Elkano's research
Mikel Elkano is a researcher in Machine Learning and Computational Neuroscience at Neuraptic AI. Their work has been cited 986 times across 27 publications (h-index 9), according to Google Scholar.
Their most-cited work, “CC-integrals: Choquet-like copula-based aggregation functions and its application in fuzzy rule-based classification systems” (2017), has accumulated 200 citations. Other influential works include “Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between-Dimensional Overlap Functions and Decomposition Strategies” (2014) with 181 citations and “Fuzzy Rule-Based Classification Systems for multi-class problems using binary decomposition strategies: On the influence of n-dimensional overlap functions in the …” (2016) with 144 citations.
Citations of Mikel Elkano's research come primarily from China, Spain and Brazil, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
