Rob Fergus Google Scholar: h-index, Total Citations, and Citation Map
Rob Fergus's h-index is 64 (96 i10-index, 167,578+ total citations across 176+ publications) according to Google Scholar as of November 2026. Rob Fergus is affiliated with New York University.
Rob Fergus is a researcher affiliated with New York University, specializing in AI & Machine Learning. Their work has been cited 167,578 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Rob Fergus's Citation Metrics
Bibliometric impact based on 176 indexed publications.
- H-Index
- 64
- i10-Index
- 96
- Total Citations
- 167,578
- Citing Countries
- 78
As of November 2026.
Rob Fergus has an h-index of 64 and 167,578 total citations across 176 publications, with research cited by institutions in 78 countries.
Global Impact Map
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Visualizing and Understanding Convolutional Networks
201426,232
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.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Rob Fergus's research
Rob Fergus is a researcher in AI & Machine Learning at New York University. Their work has been cited 167,578 times across 176 publications (h-index 64), according to Google Scholar.
Their most-cited work, “Visualizing and Understanding Convolutional Networks” (2014), has accumulated 26,232 citations. Other influential works include “Learning Spatiotemporal Features with 3D Convolutional Networks” (2015) with 9,550 citations and “Intriguing properties of neural networks” (2013) with 5,706 citations.
Citations of Rob Fergus's research come primarily from China, United States 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.
