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.
In-Band Full-Duplex Wireless: Challenges and Opportunities
20141.6k citationsAshutosh Sabharwal, Philip Schniter et al.IEEE Journal on Selected Areas in Communicationsprofile →
On the Achievable Diversity–Multiplexing Tradeoff in Half-Duplex Cooperative Channels
2005782 citationsPhilip Schniter et al.IEEE Transactions on Information Theoryprofile →
Blind equalization using the constant modulus criterion: a review
Countries citing papers authored by Philip Schniter
Since
Specialization
Citations
This map shows the geographic impact of Philip Schniter'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 Philip Schniter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip Schniter more than expected).
This network shows the impact of papers produced by Philip Schniter. 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 Philip Schniter. The network helps show where Philip Schniter may publish in the future.
Co-authorship network of co-authors of Philip Schniter
This figure shows the co-authorship network connecting the top 25 collaborators of Philip Schniter.
A scholar is included among the top collaborators of Philip Schniter 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 Philip Schniter. Philip Schniter is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Borgerding, Mark, Philip Schniter, & Sundeep Rangan. (2017). AMP-Inspired Deep Networks for Sparse Linear Inverse Problems. IEEE Transactions on Signal Processing. 65(16). 4293–4308.294 indexed citations breakdown →
Borgerding, Mark & Philip Schniter. (2016). Onsager-Corrected Deep Networks for Sparse Linear Inverse Problems.. arXiv (Cornell University).2 indexed citations
Pereyra, Marcelo, Philip Schniter, Émilie Chouzenoux, et al.. (2015). Tutorial on Stochastic Simulation and Optimization Methods in Signal Processing. arXiv (Cornell University).5 indexed citations
13.
Schniter, Philip, et al.. (2015). Iteratively Reweighted $\ell_1$ Approaches to $\ell_2$-Constrained Sparse Composite Regularization. arXiv (Cornell University).1 indexed citations
14.
Sabharwal, Ashutosh, Philip Schniter, Dongning Guo, et al.. (2014). In-Band Full-Duplex Wireless: Challenges and Opportunities. IEEE Journal on Selected Areas in Communications. 32(9). 1637–1652.1642 indexed citations breakdown →
15.
Borgerding, Mark & Philip Schniter. (2013). Generalized Approximate Message Passing for the Cosparse Analysis Model.. arXiv (Cornell University).9 indexed citations
Aggarwal, Rohit, Mohamad Assaad, C. Emre Koksal, & Philip Schniter. (2010). Optimal Joint Scheduling and Resource Allocation in OFDMA Downlink Systems with Imperfect Channel-State Information. arXiv (Cornell University).1 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.