Nitin Kohli: h-index, Total Citations, and Citation Map
Nitin Kohli's h-index is 11 (12 i10-index, 865+ total citations across 21+ publications) according to Google Scholar as of May 2026. Nitin Kohli is affiliated with UC Berkeley.
Nitin Kohli is a researcher affiliated with UC Berkeley, specializing in Privacy, Algorithms, Mechanism Design. Their work has been cited 865 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Nitin Kohli's Citation Metrics
Bibliometric impact based on 21 indexed publications.
- H-Index
- 11
- i10-Index
- 12
- Total Citations
- 865
- Citing Countries
- 9
As of May 2026.
Nitin Kohli has an h-index of 11 and 865 total citations across 21 publications, with research cited by institutions in 9 countries.
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Global Impact Map
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Top Cited Works
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Differential Privacy in Practice: Expose your Epsilons!
2019300
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.
The researcher advanced differential privacy practice by exposing epsilon values, a seminal contribution evidenced by nearly 300 citations and widespread independent adoption.
The researcher advanced the theoretical understanding of bias in automated decision-making by integrating epistemological perspectives and dynamic analysis into the discourse.
The researcher developed Epsilon Voting, a mechanism design framework for selecting differential privacy parameters, establishing a foundational approach to balancing privacy and utility in data analysis.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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