Gisele L. Pappa: h-index, Total Citations, and Citation Map
Gisele L. Pappa's h-index is 37 (91 i10-index, 4,523+ total citations across 5+ publications) according to Google Scholar as of June 2026. Gisele L. Pappa is affiliated with Computer Science, Universidade Federal de Minas Gerais.
Gisele L. Pappa is a researcher affiliated with Computer Science, Universidade Federal de Minas Gerais, specializing in Evolutionary Computation, Genetic Programming, Machine learning. Their work has been cited 4,523 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Gisele L. Pappa's Citation Metrics
Bibliometric impact based on 5 indexed publications.
- H-Index
- 37
- i10-Index
- 91
- Total Citations
- 4,523
- Citing Countries
- 16
As of June 2026.
Gisele L. Pappa has an h-index of 37 and 4,523 total citations across 5 publications, with research cited by institutions in 16 countries.
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Global Impact Map
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Adaptive normalization: A novel data normalization approach for non-stationary time series
2010295
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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 adaptive normalization for non-stationary time series, a novel approach that has garnered significant independent scholarly attention.
The researcher developed a method to infer Twitter message locations using user relationships, establishing a foundational approach for geolocation in social media analysis.
The researcher established a critical theoretical framework contrasting meta-learning with hyper-heuristics, specifically clarifying the distinct role of evolutionary algorithms in these adaptive optimization paradigms.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Gisele L. Pappa's research
Gisele L. Pappa is a researcher in Evolutionary Computation, Genetic Programming and Machine learning at Computer Science, Universidade Federal de Minas Gerais. Their work has been cited 4,523 times across 5 publications (h-index 37), according to Google Scholar.
Their most-cited work, “Adaptive normalization: A novel data normalization approach for non-stationary time series” (2010), has accumulated 295 citations. Other influential works include “Inferring the Location of Twitter Messages Based on User Relationships” (2011) with 292 citations and “Towards a unified understanding of semantic parsing” (2018) with 171 citations.
Citations of Gisele L. Pappa's research come primarily from United States, Brazil and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
