Tinghui Zhou: h-index, Total Citations, and Citation Map
Tinghui Zhou's h-index is 20 (21 i10-index, 44,225+ total citations across 33+ publications) according to Google Scholar as of June 2026. Tinghui Zhou is affiliated with Roblox, Foundation AI.
Tinghui Zhou is a researcher affiliated with Roblox, Foundation AI, specializing in Computer Vision/Graphics, Machine Learning. Their work has been cited 44,225 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Tinghui Zhou's Citation Metrics
Bibliometric impact based on 33 indexed publications.
- H-Index
- 20
- i10-Index
- 21
- Total Citations
- 44,225
- Citing Countries
- 68
As of June 2026.
Tinghui Zhou has an h-index of 20 and 44,225 total citations across 33 publications, with research cited by institutions in 68 countries.
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We've mapped 5,000 of 44,225 citations for Tinghui Zhou
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Image-to-image translation with conditional adversarial networks
201731,500
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.
745 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered unsupervised methods for learning depth and ego-motion from video, establishing a foundational framework that enabled subsequent advances in view synthesis and multiplane image processing.
The researcher pioneered conditional adversarial networks for image-to-image translation, establishing a foundational framework that enabled subsequent advancements in complex, multi-modal generative tasks such as synchronized human motion synthesis.
The researcher developed foundational methods to mitigate dataset bias, establishing a critical framework for ensuring fairness and robustness in machine learning systems.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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