Mohammad Salman Yasin: h-index, Total Citations, and Citation Map
Mohammad Salman Yasin's h-index is 9 (9 i10-index, 309+ total citations across 23+ publications) according to Google Scholar as of May 2026. Mohammad Salman Yasin is affiliated with Auburn University.
Mohammad Salman Yasin is a researcher affiliated with Auburn University, specializing in Fatigue, Fracture mechanics, Additive manufacturing. Their work has been cited 309 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Mohammad Salman Yasin's Citation Metrics
Bibliometric impact based on 23 indexed publications.
- H-Index
- 9
- i10-Index
- 9
- Total Citations
- 309
- Citing Countries
- 35
As of May 2026.
Mohammad Salman Yasin has an h-index of 9 and 309 total citations across 23 publications, with research cited by institutions in 35 countries.
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Top Cited Works
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Feature-based volumetric defect classification in metal additive manufacturing
2022160
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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.
46 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established a feature-based framework for classifying volumetric defects in metal additive manufacturing, subsequently extending this methodology to analyze fatigue-critical features and process-induced variability in Ti-6Al-4V components.
The researcher established a foundational link between powder particle size and fatigue performance in laser powder-bed fused Ti-6Al-4V, providing critical insights for optimizing additive manufacturing processes.
The researcher established a comparative framework for evaluating the fatigue performance of various additively manufactured titanium alloys, providing critical baseline data for this emerging materials domain.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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