Bryan Nousain

788 total citations · 1 hit paper
8 papers, 596 citations indexed

About

Bryan Nousain is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Bryan Nousain has authored 8 papers receiving a total of 596 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Signal Processing and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Bryan Nousain's work include Wireless Signal Modulation Classification (5 papers), Speech and Audio Processing (2 papers) and Digital Media Forensic Detection (2 papers). Bryan Nousain is often cited by papers focused on Wireless Signal Modulation Classification (5 papers), Speech and Audio Processing (2 papers) and Digital Media Forensic Detection (2 papers). Bryan Nousain collaborates with scholars based in United States. Bryan Nousain's co-authors include George Stantchev, Mark K. Hinders, Jonathan M. Nichols, F. Bucholtz and C. G. Davis and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Signal Processing and Expert Systems with Applications.

In The Last Decade

Bryan Nousain

8 papers receiving 572 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.

Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks

2018 377 citations George Stantchev, Bryan Nousain et al. IEEE Journal of Selected Topics in Signal Processing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bryan Nousain United States	5	515	265	156	155	143	8	596
Guanxiong Shen United Kingdom	11	538 1.0×	327 1.2×	152 1.0×	247 1.6×	112 0.8×	20	738
Mauro Belgiovine United States	7	439 0.9×	287 1.1×	146 0.9×	123 0.8×	91 0.6×	15	559
Fanggang Wang China	14	460 0.9×	331 1.2×	204 1.3×	118 0.8×	80 0.6×	42	722
Jeyanthi Hall Canada	6	310 0.6×	182 0.7×	68 0.4×	122 0.8×	81 0.6×	7	456
Kemal Davaslıoğlu United States	16	385 0.7×	387 1.5×	86 0.6×	88 0.6×	46 0.3×	37	740
Caidan Zhao China	13	192 0.4×	151 0.6×	99 0.6×	59 0.4×	97 0.7×	44	386
Van‐Phuc Hoang Vietnam	11	196 0.4×	184 0.7×	54 0.3×	78 0.5×	92 0.6×	85	472
Sebastian Dörner Germany	7	410 0.8×	485 1.8×	123 0.8×	97 0.6×	30 0.2×	15	685
Haijun Tan China	9	109 0.2×	192 0.7×	75 0.5×	57 0.4×	53 0.4×	15	322
Haji M. Furqan Türkiye	11	176 0.3×	716 2.7×	206 1.3×	38 0.2×	106 0.7×	26	836

Countries citing papers authored by Bryan Nousain

Since Specialization

Citations

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

Fields of papers citing papers by Bryan Nousain

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bryan Nousain

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

All Works

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8 of 8 papers shown

1.

Nousain, Bryan, et al.. (2019). Enhanced RF Fingerprinting for IoT Devices with Recurrent Neural Networks. 590–597. 18 indexed citations

2.

Nousain, Bryan, et al.. (2019). Toward Receiver-Agnostic RF Fingerprint Verification. 1–6. 18 indexed citations

3.

Nousain, Bryan, et al.. (2019). Securing IoT RF Fingerprinting Systems with Generative Adversarial Networks. 584–589. 15 indexed citations

4.

Davis, C. G., et al.. (2018). Alias-Free Products of Signals Near Nyquist Rate. IEEE Transactions on Signal Processing. 66(16). 4151–4159. 1 indexed citations

5.

Stantchev, George, et al.. (2018). Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks. IEEE Journal of Selected Topics in Signal Processing. 12(1). 160–167. 377 indexed citations breakdown →

6.

Nousain, Bryan, et al.. (2012). Frequency position modulation using multi-spectral projections. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8514. 85140C–85140C. 1 indexed citations

7.

Nichols, Jonathan M., F. Bucholtz, & Bryan Nousain. (2011). Automated, rapid classification of signals using locally linear embedding. Expert Systems with Applications. 38(10). 13472–13474. 4 indexed citations

8.

Nousain, Bryan, et al.. (2011). Wavelet Fingerprinting of Radio-Frequency Identification (RFID) Tags. IEEE Transactions on Industrial Electronics. 59(12). 4843–4850. 162 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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