Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Linear precoding via conic optimization for fixed MIMO receivers
2005733 citationsAmi Wiesel, Yonina C. Eldar et al.IEEE Transactions on Signal Processingprofile →
Zero-Forcing Precoding and Generalized Inverses
2008422 citationsAmi Wiesel, Yonina C. Eldar et al.IEEE Transactions on Signal Processingprofile →
Dynamic reconfiguration of the default mode network during narrative comprehension
2016375 citationsErez Simony, Christopher J. Honey et al.Nature Communicationsprofile →
Learning to Detect
2019340 citationsTzvi Diskin, Ami Wiesel et al.IEEE Transactions on Signal Processingprofile →
Shrinkage Algorithms for MMSE Covariance Estimation
2010324 citationsYilun Chen, Ami Wiesel et al.IEEE Transactions on Signal Processingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Ami Wiesel's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ami Wiesel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ami Wiesel more than expected).
This network shows the impact of papers produced by Ami Wiesel. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ami Wiesel. The network helps show where Ami Wiesel may publish in the future.
Co-authorship network of co-authors of Ami Wiesel
This figure shows the co-authorship network connecting the top 25 collaborators of Ami Wiesel.
A scholar is included among the top collaborators of Ami Wiesel based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Ami Wiesel. Ami Wiesel is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Simony, Erez, Christopher J. Honey, Janice Chen, et al.. (2016). Dynamic reconfiguration of the default mode network during narrative comprehension. Nature Communications. 7(1). 12141–12141.375 indexed citations breakdown →
11.
Wiesel, Ami & Teng Zhang. (2015). Structured Robust Covariance Estimation. Journal of International Crisis and Risk Communication Research. 8(3). 127–216.23 indexed citations
Meng, Zhaoshi, Dennis Wei, Ami Wiesel, & Alfred O. Hero. (2013). Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods. International Conference on Artificial Intelligence and Statistics. 39–47.15 indexed citations
Chen, Yilun, Ami Wiesel, Yonina C. Eldar, & Alfred O. Hero. (2010). Shrinkage Algorithms for MMSE Covariance Estimation. IEEE Transactions on Signal Processing. 58(10). 5016–5029.324 indexed citations breakdown →
Wiesel, Ami, Luis G. Uzeda Garcia, Jorge Garcı́a-Vidal, Albert Pagès, & J.R. Fonollosa. (2003). Turbo Linear Dispersion Space Time Coding for MIMO HSDPA Systems.3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.