Jaya Vardhani Mamidala: h-index, Total Citations, and Citation Map
Jaya Vardhani Mamidala's h-index is 17 (21 i10-index, 609+ total citations across 10+ publications) according to Google Scholar as of May 2026. Jaya Vardhani Mamidala is affiliated with Senior Software Engineer, Microsoft Corporation.
Jaya Vardhani Mamidala is a researcher affiliated with Senior Software Engineer, Microsoft Corporation, specializing in Artificial Intelligence, Machine Learning, Security and Compliance. Their work has been cited 609 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Jaya Vardhani Mamidala's Citation Metrics
Bibliometric impact based on 10 indexed publications. Of these, 6 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 17
- i10-Index
- 21
- Total Citations
- 609
- Citing Countries
- 4
As of May 2026.
Jaya Vardhani Mamidala has an h-index of 17 and 609 total citations across 10 publications, with research cited by institutions in 4 countries.
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Top Cited Works
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Enhancing Cloud Infrastructure Security Through AI-Powered Big Data Anomaly Detection
202150
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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.
109 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed an AI-powered big data anomaly detection framework to enhance cloud infrastructure security, a contribution validated by independent scholarly uptake.
The researcher established a foundational framework for applying artificial intelligence to liquidity risk management, identifying critical challenges and future research directions in a widely cited 2021 survey.
The researcher published a seminal 2021 paper that has garnered 30 citations, establishing a foundational contribution recognized by independent scholars in the field.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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