Mengqi Yao: h-index, Total Citations, and Citation Map
Mengqi Yao's h-index is 9 (9 i10-index, 351+ total citations across 5+ publications) according to Google Scholar as of May 2026. Mengqi Yao is affiliated with Unknown affiliation.
Mengqi Yao is a researcher affiliated with Unknown affiliation, specializing in Power System, Data-Driven. Their work has been cited 351 times. This profile visualizes their global influence, highlighting strong citation networks in Thailand.
Mengqi Yao's Citation Metrics
Bibliometric impact based on 5 indexed publications. Of these, 4 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 9
- i10-Index
- 9
- Total Citations
- 351
- Citing Countries
- 2
As of May 2026.
Mengqi Yao has an h-index of 9 and 351 total citations across 5 publications, with research cited by institutions in 2 countries.
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Top Cited Works
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An optimal power-flow approach to improve power system voltage stability using demand response
201981
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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 an optimal power-flow approach integrating demand response to enhance voltage stability in power systems, a method that has garnered significant independent academic attention.
The researcher developed methods for mitigating voltage unbalance using distributed solar photovoltaic inverters, a contribution evidenced by a seminal 2020 paper with 65 citations.
The researcher developed a data-driven strategy for optimal power system decision-making during wildfire events, addressing critical grid resilience challenges.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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