Honglak Lee Google Scholar: h-index, Total Citations, and Citation Map
Honglak Lee's h-index is 106 (205 i10-index, 84,728+ total citations across 283+ publications) according to Google Scholar as of October 2026. Honglak Lee is affiliated with LG AI Research / U. Michigan.
Honglak Lee is a researcher affiliated with LG AI Research / U. Michigan, specializing in various fields. Their work has been cited 84,728 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Honglak Lee's Citation Metrics
Bibliometric impact based on 283 indexed publications.
- H-Index
- 106
- i10-Index
- 205
- Total Citations
- 84,728
- Citing Countries
- 66
As of October 2026.
Honglak Lee has an h-index of 106 and 84,728 total citations across 283 publications, with research cited by institutions in 66 countries.
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An analysis of single-layer networks in unsupervised feature learning
20115,818
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
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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.
17 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed efficient sparse coding algorithms and extended this framework to model visual area V2 using sparse deep belief nets, establishing a foundational approach to hierarchical sparse representations in computational neuroscience.
The researcher advanced fine-grained image classification by developing output embedding techniques and extending them to visual descriptions, establishing a widely adopted framework for detailed visual recognition.
The researcher advanced unsupervised feature learning by analyzing single-layer networks, establishing a foundational framework widely adopted by the independent research community.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Honglak Lee's research
Honglak Lee is a researcher at LG AI Research / U. Michigan. Their work has been cited 84,728 times across 283 publications (h-index 106), according to Google Scholar.
Their most-cited work, “An analysis of single-layer networks in unsupervised feature learning” (2011), has accumulated 5,818 citations. Other influential works include “Learning structured output representation using deep conditional generative models” (2015) with 5,178 citations and “Multimodal deep learning” (2011) with 5,142 citations.
Citations of Honglak Lee'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.
