Aditya Khosla Google Scholar: h-index, Total Citations, and Citation Map
Aditya Khosla's h-index is 38 (44 i10-index, 112,677+ total citations across 70+ publications) according to Google Scholar as of October 2026. Aditya Khosla is affiliated with CTO, Iterative Health.
Aditya Khosla is a researcher affiliated with CTO, Iterative Health, specializing in Computer Vision, Machine Learning, Medical Imaging. Their work has been cited 112,677 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Aditya Khosla's Citation Metrics
Bibliometric impact based on 70 indexed publications.
- H-Index
- 38
- i10-Index
- 44
- Total Citations
- 112,677
- Citing Countries
- 59
As of October 2026.
Aditya Khosla has an h-index of 38 and 112,677 total citations across 70 publications, with research cited by institutions in 59 countries.
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Global Impact Map
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Imagenet large scale visual recognition challenge
201555,684
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.
9 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established foundational benchmarks for large-scale visual recognition and advanced discriminative localization and scene understanding through highly cited, independent work.
The researcher developed an integrated machine learning framework for stroke prediction, establishing a foundational approach that has been widely adopted by the independent scientific community.
The researcher established a foundational framework for multimodal deep learning, a seminal contribution that has been widely adopted and cited by the global machine learning community.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Aditya Khosla's research
Aditya Khosla is a researcher in Computer Vision, Machine Learning and Medical Imaging at CTO, Iterative Health. Their work has been cited 112,677 times across 70 publications (h-index 38), according to Google Scholar.
Their most-cited work, “Imagenet large scale visual recognition challenge” (2015), has accumulated 55,684 citations. Other influential works include “Learning deep features for discriminative localization” (2016) with 15,605 citations and “3d shapenets: A deep representation for volumetric shapes” (2015) with 8,734 citations.
Citations of Aditya Khosla's research come primarily from United States, China 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.
