Gang YU Google Scholar: h-index, Total Citations, and Citation Map
Gang YU's h-index is 14 (19 i10-index, 33,305+ total citations across 20+ publications) according to Google Scholar as of October 2026. Gang YU is affiliated with StepFun.
Gang YU is a researcher affiliated with StepFun, specializing in various fields. Their work has been cited 33,305 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Gang YU's Citation Metrics
Bibliometric impact based on 20 indexed publications.
- H-Index
- 14
- i10-Index
- 19
- Total Citations
- 33,305
- Citing Countries
- 53
As of October 2026.
Gang YU has an h-index of 14 and 33,305 total citations across 20 publications, with research cited by institutions in 53 countries.
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Robust performance degradation assessment methods for enhanced rolling element bearing prognostics
2003424
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.
1 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed a novel statistical framework using alpha-stable distributions for rolling element bearing fault detection, establishing a foundational method for robust diagnostic modeling in noisy industrial environments.
The researcher developed an analytical framework for monitoring tool wear in turning operations using ultrasound, subsequently advancing the methodology with wavelet analysis to enhance precision.
The researcher developed robust methods for assessing performance degradation in rolling element bearings, significantly enhancing prognostic accuracy and reliability in mechanical systems.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Gang YU's research
Gang YU is a researcher at StepFun. Their work has been cited 33,305 times across 20 publications (h-index 14), according to Google Scholar.
Their most-cited work, “Robust performance degradation assessment methods for enhanced rolling element bearing prognostics” (2003), has accumulated 424 citations. Other influential works include “A time-frequency spectral amplitude modulation method and its applications in rolling bearing fault diagnosis” (2022) with 142 citations and “A Zero-Voltage-Switching Bidirectional DC–DC Converter With State Analysis and Soft-Switching-Oriented Design Consideration” (2009) with 136 citations.
Citations of Gang YU's research come primarily from China, United States 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.
