Aurélien Decelle: h-index, Total Citations, and Citation Map
Aurélien Decelle's h-index is 22 (39 i10-index, 2,888+ total citations across 5+ publications) according to Google Scholar as of May 2026. Aurélien Decelle is affiliated with Research, Universidad Politécnica de Madrid.
Aurélien Decelle is a researcher affiliated with Research, Universidad Politécnica de Madrid, specializing in statistical physics, machine learning, Bayesian inference. Their work has been cited 2,888 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Aurélien Decelle's Citation Metrics
Bibliometric impact based on 5 indexed publications. Of these, 4 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 22
- i10-Index
- 39
- Total Citations
- 2,888
- Citing Countries
- 21
As of May 2026.
Aurélien Decelle has an h-index of 22 and 2,888 total citations across 5 publications, with research cited by institutions in 21 countries.
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Top Cited Works
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Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
20111,030
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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 established a theoretical framework for detecting modules in sparse networks, characterizing the inference limits and phase transitions that define detectability in complex systems.
The researcher established a theoretical framework linking Archimedean lattices to the bound states of wave-interacting particles, a contribution recognized by 90 citations.
The researcher established a foundational asymptotic framework for analyzing modular networks via the stochastic block model, enabling rigorous algorithmic applications in community detection.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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