Zhengqi Li: h-index, Total Citations, and Citation Map
Zhengqi Li's h-index is 24 (29 i10-index, 6,182+ total citations across 50+ publications) according to Google Scholar as of June 2026. Zhengqi Li is affiliated with Google DeepMind.
Zhengqi Li is a researcher affiliated with Google DeepMind, specializing in various fields. Their work has been cited 6,182 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Zhengqi Li's Citation Metrics
Bibliometric impact based on 50 indexed publications.
- H-Index
- 24
- i10-Index
- 29
- Total Citations
- 6,182
- Citing Countries
- 23
As of June 2026.
Zhengqi Li has an h-index of 24 and 6,182 total citations across 50 publications, with research cited by institutions in 23 countries.
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MegaDepth: Learning Single-View Depth Prediction from Internet Photos
20181,730
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 pioneered neural methods for dynamic scene understanding, establishing a foundational framework for synthesizing and rendering moving subjects from static observations.
The researcher advanced single-view depth prediction by leveraging large-scale internet photo data, establishing a foundational approach widely adopted by independent computer vision researchers.
The researcher advanced computer vision by publishing a seminal 2023 ICCV paper on comprehensive object tracking, establishing a foundational approach widely adopted by independent scholars.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Zhengqi Li's research
Zhengqi Li is a researcher at Google DeepMind. Their work has been cited 6,182 times across 50 publications (h-index 24), according to Google Scholar.
Their most-cited work, “MegaDepth: Learning Single-View Depth Prediction from Internet Photos” (2018), has accumulated 1,730 citations. Other influential works include “Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes” (2021) with 1,130 citations and “DynIBaR: Neural Dynamic Image-Based Rendering” (2023) with 352 citations.
Citations of Zhengqi Li's research come primarily from China, United States and Hong Kong, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
