Tong Zhang: h-index, Total Citations, and Citation Map
Tong Zhang's h-index is 149 (769 i10-index, 87,426+ total citations across 1,000+ publications) according to Google Scholar as of September 2026. Tong Zhang is affiliated with UIUC.
Tong Zhang is a researcher affiliated with UIUC, specializing in Machine Learning. Their work has been cited 87,426 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Tong Zhang's Citation Metrics
Bibliometric impact based on 1,000 indexed publications.
- H-Index
- 149
- i10-Index
- 769
- Total Citations
- 87,426
- Citing Countries
- 97
As of September 2026.
Tong Zhang has an h-index of 149 and 87,426 total citations across 1000 publications, with research cited by institutions in 97 countries.
Global Impact Map
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Accelerating stochastic gradient descent using predictive variance reduction
20133,831
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.
1220 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed MA-LoT, a model-collaboration framework for long chain-of-thought reasoning in formal theorem proving, subsequently extending this methodology to physics domains.
The researcher advanced large-scale linear prediction by applying stochastic gradient descent algorithms, a foundational contribution evidenced by nearly 1,700 citations.
The researcher established foundational theoretical guarantees for convex risk minimization in classification, providing rigorous proofs of statistical consistency that underpin modern machine learning algorithms.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Tong Zhang's research
Tong Zhang is a researcher in Machine Learning at UIUC. Their work has been cited 87,426 times across 1,000 publications (h-index 149), according to Google Scholar.
Their most-cited work, “Accelerating stochastic gradient descent using predictive variance reduction” (2013), has accumulated 3,831 citations. Other influential works include “A framework for learning predictive structures from multiple tasks and unlabeled data.” (2005) with 1,930 citations and “Solving large scale linear prediction problems using stochastic gradient descent algorithms” (2004) with 1,700 citations.
Citations of Tong Zhang'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.
