Mark Borgerding

565 total citations · 1 hit paper
7 papers, 362 citations indexed

About

Mark Borgerding is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Mark Borgerding has authored 7 papers receiving a total of 362 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computational Mechanics, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Mark Borgerding's work include Sparse and Compressive Sensing Techniques (3 papers), Manufacturing Process and Optimization (2 papers) and Image and Signal Denoising Methods (2 papers). Mark Borgerding is often cited by papers focused on Sparse and Compressive Sensing Techniques (3 papers), Manufacturing Process and Optimization (2 papers) and Image and Signal Denoising Methods (2 papers). Mark Borgerding collaborates with scholars based in United States and Germany. Mark Borgerding's co-authors include Philip Schniter, Sundeep Rangan, Jeremy Vila and Peter Nyhuis and has published in prestigious journals such as IEEE Transactions on Signal Processing, IEEE Access and IEEE Signal Processing Magazine.

In The Last Decade

Mark Borgerding

6 papers receiving 345 citations

Hit Papers

align trajectories

What are hit papers?

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.

AMP-Inspired Deep Networks for Sparse Linear Inverse Problems

2017 294 citations Mark Borgerding, Philip Schniter et al. IEEE Transactions on Signal Processing profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mark Borgerding United States	4	167	164	88	78	66	7	362
Farzan Haddadi Iran	9	81 0.5×	101 0.6×	64 0.7×	55 0.7×	103 1.6×	28	284
Justin Ziniel United States	8	203 1.2×	387 2.4×	116 1.3×	76 1.0×	194 2.9×	12	536
Masoumeh Azghani Iran	10	86 0.5×	134 0.8×	126 1.4×	49 0.6×	63 1.0×	38	285
Lorne Applebaum United States	7	126 0.8×	255 1.6×	107 1.2×	42 0.5×	103 1.6×	9	318
Kfir Gedalyahu Israel	5	77 0.5×	233 1.4×	114 1.3×	88 1.1×	139 2.1×	8	338
Shuhong Jiao China	10	68 0.4×	76 0.5×	51 0.6×	87 1.1×	58 0.9×	35	278
Ali Hormati Switzerland	9	194 1.2×	161 1.0×	94 1.1×	38 0.5×	98 1.5×	21	384
Scott Pudlewski United States	12	239 1.4×	183 1.1×	63 0.7×	140 1.8×	79 1.2×	33	505
Gerald L. Fudge United States	8	97 0.6×	171 1.0×	75 0.9×	43 0.6×	111 1.7×	20	286
Yechao Bai China	10	83 0.5×	65 0.4×	71 0.8×	95 1.2×	57 0.9×	55	346

Countries citing papers authored by Mark Borgerding

Since Specialization

Citations

This map shows the geographic impact of Mark Borgerding'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 Mark Borgerding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Borgerding more than expected).

Fields of papers citing papers by Mark Borgerding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Borgerding. 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 Mark Borgerding. The network helps show where Mark Borgerding may publish in the future.

Co-authorship network of co-authors of Mark Borgerding

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Borgerding. A scholar is included among the top collaborators of Mark Borgerding 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 Mark Borgerding. Mark Borgerding is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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7 of 7 papers shown

1.

Borgerding, Mark, et al.. (2025). Combination of synchronised assembly precedence matrices. The International Journal of Advanced Manufacturing Technology.

2.

Borgerding, Mark, et al.. (2025). Assembly Sequence Flexibility – Assembly Precedence Matrix-Based Evaluation Model. IEEE Access. 13. 115002–115017. 1 indexed citations

3.

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 →

4.

Borgerding, Mark & Philip Schniter. (2016). Onsager-Corrected Deep Networks for Sparse Linear Inverse Problems.. arXiv (Cornell University). 2 indexed citations

5.

Borgerding, Mark, Philip Schniter, Jeremy Vila, & Sundeep Rangan. (2015). Generalized approximate message passing for cosparse analysis compressive sensing. 10. 3756–3760. 17 indexed citations

6.

Borgerding, Mark & Philip Schniter. (2013). Generalized Approximate Message Passing for the Cosparse Analysis Model.. arXiv (Cornell University). 9 indexed citations

7.

Borgerding, Mark. (2006). Turning overlap-save into a multiband mixing, downsampling filter bank. IEEE Signal Processing Magazine. 23(2). 158–161. 39 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.

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