Shih-Fu Chang Google Scholar: h-index, Total Citations, and Citation Map
Shih-Fu Chang's h-index is 144 (598 i10-index, 130,107+ total citations across 1,000+ publications) according to Google Scholar as of November 2026. Shih-Fu Chang is affiliated with Columbia University.
Shih-Fu Chang is a researcher affiliated with Columbia University, specializing in Multimedia, Computer Vision, Machine Learning. Their work has been cited 130,107 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Shih-Fu Chang's Citation Metrics
Bibliometric impact based on 1,000 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 144
- i10-Index
- 598
- Total Citations
- 130,107
- Citing Countries
- 67
As of November 2026.
Shih-Fu Chang has an h-index of 144 and 130,107 total citations across 1000 publications, with research cited by institutions in 67 countries.
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Global Impact Map
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Fast r-cnn
201547,003
Top Citing Countries
Top Citing Institutions
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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.
1563 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established a foundational framework for fully automated, content-based visual media retrieval, extending from image queries to spatiotemporal video search.
The researcher established a foundational framework for supervised hashing with kernels, subsequently advancing the field through discrete graph-based methods.
The researcher established a foundational framework for fast object detection and extended it to temporal action localization in untrimmed videos.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Shih-Fu Chang's research
Shih-Fu Chang is a researcher in Multimedia, Computer Vision and Machine Learning at Columbia University. Their work has been cited 130,107 times across 1,000 publications (h-index 144), according to Google Scholar.
Their most-cited work, “Fast r-cnn” (2015), has accumulated 47,003 citations. Other influential works include “Image retrieval: Current techniques, promising directions, and open issues” (1999) with 3,656 citations and “VisualSEEk: a fully automated content-based image query system” (1997) with 3,060 citations.
Citations of Shih-Fu Chang's research come primarily from China, United States and India, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
