Tomislav Lipic: h-index, Total Citations, and Citation Map
Tomislav Lipic's h-index is 18 (26 i10-index, 2,081+ total citations across 5+ publications) according to Google Scholar as of May 2026. Tomislav Lipic is affiliated with Ruđer Bošković Institute.
Tomislav Lipic is a researcher affiliated with Ruđer Bošković Institute, specializing in Complex Networks, Deep Learning, Artificial Intelligence. Their work has been cited 2,081 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Tomislav Lipic's Citation Metrics
Bibliometric impact based on 5 indexed publications.
- H-Index
- 18
- i10-Index
- 26
- Total Citations
- 2,081
- Citing Countries
- 15
As of May 2026.
Tomislav Lipic has an h-index of 18 and 2,081 total citations across 5 publications, with research cited by institutions in 15 countries.
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Global Impact Map
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Top Cited Works
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Social physics
2022690
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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 advanced fine art classification via CNN fine-tuning and expanded into social physics, establishing a highly cited, independently validated research trajectory.
The researcher developed a 4D thermal imaging system for medical applications, establishing a foundational framework for spatiotemporal thermal analysis in clinical settings.
The researcher pioneered a deep learning framework for analyzing aesthetic, emotional, and mnemonic dimensions of art, establishing a foundational approach for computational art interpretation.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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