Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
2006 • 20874 Citations
Published in IEEE Transactions on Information Theory
Terence Tao
Terence Tao is a researcher affiliated with Professor of Mathematics, UCLA, specializing in Mathematics. Their work has been cited 108,749 times. This profile visualizes their global influence, highlighting strong citation networks in CN.
Mathematics
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Terence Tao's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 108,749
- Citing Countries
- 7
As of April 2026.
Terence Tao has an h-index of 1 and 108,749 total citations across 1 publication, with research cited by institutions in 7 countries.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
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Top Citing Countries(Limited)
China(CN)
8Germany(DE)
5Switzerland(CH)
4United States(US)
3France(FR)
1United Kingdom(GB)
1Singapore(SG)
1Top Citing Institutions(Limited)
Southeast University
5École polytechnique fédérale de Lausanne (EPFL)
4University of Siegen
4University of Washington
2Nanchang University
2National University of Singapore
1Queen Mary University of London
1University of California, Irvine
1The Chinese University of Hong Kong
1Friedrich-Alexander-University Erlangen-Nürnberg
1Visa 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.
Citer Influence Network
Visa-ready visualisation: each outer ring node is a country citing this scholar. Node size & edge weight scale with citing-paper count. Showing top 7 of 7 countries (23 total citations).
Letter of Support — Candidate Recommenders
Ranked by EB-1A / O-1A relevance: independence from your home institution, affiliation with a top-ranked institution, repeat citations of your work, and recency. Reach out to the highest-scoring candidates to request support letters.
- #1
Michael Unser
7.0École polytechnique fédérale de Lausanne (EPFL)
Switzerland· Cited your work 1 time
IndependentTop institution - #2
Kyong Hwan Jin
7.0École polytechnique fédérale de Lausanne (EPFL)
Switzerland· Cited your work 1 time
IndependentTop institution - #3
Steven L. Brunton
7.0University of Washington
USA· Cited your work 1 time
IndependentTop institution - #4
J. Nathan Kutz
7.0University of Washington
USA· Cited your work 1 time
IndependentTop institution - #5
Angela Yingjun Zhang
7.0The Chinese University of Hong Kong
China· Cited your work 1 time
IndependentTop institution - #6
Rui Zhang
8.5National University of Singapore
Singapore· Cited your work 1 time
IndependentTop institutionDiversifies geography - #7
Yijin Pan
5.0Southeast University
China· Cited your work 1 time
Independent - #8
Hartmut Bauermeister
5.0University of Siegen
Germany· Cited your work 1 time
Independent - #9
Michael Moeller
5.0University of Siegen
Germany· Cited your work 1 time
Independent - #10
Marco Di Renzo
6.5Université Paris-Saclay
France· Cited your work 1 time
IndependentDiversifies geography
Scores combine 5 signals: independence (+3), prestige institution (+2), repeat citations (+2 per paper, cap 5), recent activity (+1), and geography diversity (+1.5). Identity matching uses name + institution; namesakes at the same org are merged.
Cited by 5 papers
5 / 5 independent
Citations flagged as non-independent share the scholar's home institution (University of California, Los Angeles (UCLA)). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
Cunhua Pan, Gui Zhou, Kangda Zhi, Sheng Hong + 7 more
IEEE Journal of Selected Topics in Signal Processing· cites “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information”
Bowen Zhang, Lingfeng Liu
Mathematics· cites “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information”
Steven L. Brunton, J. Nathan Kutz
Cambridge University Press· cites “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information”
Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller
34th Conference on Neural Information Processing Systems (NeurIPS 2020)· cites “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information”
Kyong Hwan Jin, Michael T. McCann, Emmanuel Froustey, Michael Unser
IEEE Transactions on Image Processing· cites “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information”
Top Cited Works(Showing 1 of 1)
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