María José Del Jesus Díaz: h-index, Total Citations, and Citation Map
María José Del Jesus Díaz's h-index is 47 (110 i10-index, 12,526+ total citations across 2+ publications) according to Google Scholar as of May 2026. María José Del Jesus Díaz is affiliated with Associate professor of Computer Science, University of Jaén.
María José Del Jesus Díaz is a researcher affiliated with Associate professor of Computer Science, University of Jaén, specializing in Artificial Intelligence, Data Mining, Evolutionary Fuzzy Systems. Their work has been cited 12,526 times. This profile visualizes their global influence, highlighting strong citation networks in Spain.
María José Del Jesus Díaz's Citation Metrics
Bibliometric impact based on 2 indexed publications.
- H-Index
- 47
- i10-Index
- 110
- Total Citations
- 12,526
- Citing Countries
- 11
As of May 2026.
María José Del Jesus Díaz has an h-index of 47 and 12,526 total citations across 2 publications, with research cited by institutions in 11 countries.
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We've mapped 5,000 of 12,526 citations for María José Del Jesus Díaz
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Top Cited Works
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KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems
20091,843
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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.
The researcher advanced fuzzy rule-based classification by proposing novel reasoning methods, a foundational contribution evidenced by over 550 citations and broad independent adoption.
The researcher developed KEEL, a seminal software tool for assessing evolutionary algorithms in data mining, establishing a standardized benchmarking framework widely adopted by the independent research community.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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