Cristopher Moore: h-index, Total Citations, and Citation Map
Cristopher Moore's h-index is 67 (166 i10-index, 31,645+ total citations across 4+ publications) according to Google Scholar as of May 2026. Cristopher Moore is affiliated with Santa Fe Institute.
Cristopher Moore is a researcher affiliated with Santa Fe Institute, specializing in complex networks, networks, quantum computing. Their work has been cited 31,645 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Cristopher Moore's Citation Metrics
Bibliometric impact based on 4 indexed publications. Of these, 1 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 67
- i10-Index
- 166
- Total Citations
- 31,645
- Citing Countries
- 21
As of May 2026.
Cristopher Moore has an h-index of 67 and 31,645 total citations across 4 publications, with research cited by institutions in 21 countries.
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We've mapped 5,000 of 31,645 citations for Cristopher Moore
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Global Impact Map
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Top Cited Works
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Finding community structure in very large networks
200410,378
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.
The researcher established a foundational framework linking epidemic dynamics to percolation theory in small-world networks, significantly advancing the understanding of complex network structures.
The researcher developed a seminal method for identifying community structure in very large networks, establishing a foundational approach widely adopted across scientific disciplines.
The researcher developed a hierarchical framework for predicting missing links in complex networks, establishing a foundational method for network structure analysis.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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