Rajendra Acharya Google Scholar: h-index, Total Citations, and Citation Map
Rajendra Acharya's h-index is 230 (971 i10-index, 121,449+ total citations across 1,000+ publications) according to Google Scholar as of November 2026. Rajendra Acharya is affiliated with University of Southern Queensland, Australia.
Rajendra Acharya is a researcher affiliated with University of Southern Queensland, Australia, specializing in Artificial Intelligence, Computational Intelligence, Data Science. Their work has been cited 121,449 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Rajendra Acharya's Citation Metrics
Bibliometric impact based on 1,000 indexed publications. Of these, 11 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 230
- i10-Index
- 971
- Total Citations
- 121,449
- Citing Countries
- 116
As of November 2026.
Rajendra Acharya has an h-index of 230 and 121,449 total citations across 1000 publications, with research cited by institutions in 116 countries.
Global Impact Map
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A review of uncertainty quantification in deep learning: Techniques, applications and challenges
20213,800
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.
2703 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered the application of entropy-based metrics for epilepsy detection in EEG signals, establishing a foundational methodological framework widely adopted by the independent scientific community.
The researcher developed a hybrid signal processing framework combining PCA, LDA, ICA, and wavelet transforms for ECG beat classification, establishing a widely adopted methodological standard in cardiac signal analysis.
The researcher developed a deep convolutional neural network model for heartbeat classification, establishing a foundational approach in cardiac signal analysis that has been widely adopted by the independent scientific community.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Rajendra Acharya's research
Rajendra Acharya is a researcher in Artificial Intelligence, Computational Intelligence and Data Science at University of Southern Queensland, Australia. Their work has been cited 121,449 times across 1,000 publications (h-index 230), according to Google Scholar.
Their most-cited work, “A review of uncertainty quantification in deep learning: Techniques, applications and challenges” (2021), has accumulated 3,800 citations. Other influential work includes “Heart rate variability: a review” (2006) with 3,264 citations.
Citations of Rajendra Acharya's research come primarily from China, United States and India, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
