Jacob Steinhardt: h-index, Total Citations, and Citation Map
Jacob Steinhardt's h-index is 68 (112 i10-index, 53,445+ total citations across 189+ publications) according to Google Scholar as of August 2026. Jacob Steinhardt is affiliated with Stanford University.
Jacob Steinhardt is a researcher affiliated with Stanford University, specializing in Machine learning, Statistics. Their work has been cited 53,445 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Jacob Steinhardt's Citation Metrics
Bibliometric impact based on 189 indexed publications.
- H-Index
- 68
- i10-Index
- 112
- Total Citations
- 53,445
- Citing Countries
- 75
As of August 2026.
Jacob Steinhardt has an h-index of 68 and 53,445 total citations across 189 publications, with research cited by institutions in 75 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Jacob Steinhardt's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Measuring massive multitask language understanding
202010,476
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.
1274 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established a foundational framework for evaluating large language models, pioneering systematic approaches to measure multitask understanding and analyze qualitative model behaviors.
The researcher advanced AI alignment and interpretability by establishing frameworks for value alignment and developing metrics for model competence and explanation simulatability.
The researcher pioneered the analysis of LLM safety training failures, establishing a foundational framework for understanding how adversarial inputs bypass security measures.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.
About Jacob Steinhardt's research
Jacob Steinhardt is a researcher in Machine learning and Statistics at Stanford University. Their work has been cited 53,445 times across 189 publications (h-index 68), according to Google Scholar.
Their most-cited work, “Measuring massive multitask language understanding” (2020), has accumulated 10,476 citations. Other influential works include “Measuring mathematical problem solving with the math dataset” (2021) with 6,107 citations and “Concrete problems in AI safety” (2016) with 5,733 citations.
Citations of Jacob Steinhardt's research come primarily from United States, China 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.
