Nicolas Savy: h-index, Total Citations, and Citation Map
Nicolas Savy's h-index is 17 (30 i10-index, 1,183+ total citations across 5+ publications) according to Google Scholar as of May 2026. Nicolas Savy is affiliated with Institut de mathématiques de Toulouse.
Nicolas Savy is a researcher affiliated with Institut de mathématiques de Toulouse, specializing in various fields. Their work has been cited 1,183 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Nicolas Savy's Citation Metrics
Bibliometric impact based on 5 indexed publications.
- H-Index
- 17
- i10-Index
- 30
- Total Citations
- 1,183
- Citing Countries
- 13
As of May 2026.
Nicolas Savy has an h-index of 17 and 1,183 total citations across 5 publications, with research cited by institutions in 13 countries.
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Top Cited Works
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General Model, Based on Two Mixed Weibull Distributions of Bacterial Resistance, for Describing Various Shapes of Inactivation Curves
2006253
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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 developed a general model using two mixed Weibull distributions to describe bacterial resistance and various inactivation curve shapes, establishing a foundational framework for microbial inactivation kinetics.
The researcher established a Weibull-based framework for modeling bacterial spore survival under heat, quantifying how environmental factors influence kinetic parameters to improve food safety predictions.
The researcher established sharp large deviation principles for the fractional Ornstein–Uhlenbeck process, providing a rigorous asymptotic framework for analyzing rare events in this non-Markovian stochastic system.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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