Hayreddin Çeker: h-index, Total Citations, and Citation Map
Hayreddin Çeker's h-index is 9 (9 i10-index, 465+ total citations across 19+ publications) according to Google Scholar as of May 2026. Hayreddin Çeker is affiliated with Applied Scientist @ Amazon.
Hayreddin Çeker is a researcher affiliated with Applied Scientist @ Amazon, specializing in LLMs, Agents. Their work has been cited 465 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Hayreddin Çeker's Citation Metrics
Bibliometric impact based on 19 indexed publications.
- H-Index
- 9
- i10-Index
- 9
- Total Citations
- 465
- Citing Countries
- 24
As of May 2026.
Hayreddin Çeker has an h-index of 9 and 465 total citations across 19 publications, with research cited by institutions in 24 countries.
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Global Impact Map
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Top Cited Works
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Shared keystroke dataset for continuous authentication
2016121
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.
227 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced keystroke dynamics authentication by integrating Gaussian mixture models, establishing shared datasets, and applying convolutional neural networks for sensitivity analysis.
The researcher developed a deception-based game theoretical framework to mitigate Denial-of-Service attacks, establishing a novel strategic approach to network security defense.
The researcher demonstrated that popularity metrics do not equate to influence, challenging conventional assumptions about information spread in news systems.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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