Nauman Shahid

766 total citations
22 papers, 517 citations indexed

About

Nauman Shahid is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computational Mechanics. According to data from OpenAlex, Nauman Shahid has authored 22 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 8 papers in Computer Networks and Communications and 7 papers in Computational Mechanics. Recurrent topics in Nauman Shahid's work include Anomaly Detection Techniques and Applications (8 papers), Sparse and Compressive Sensing Techniques (7 papers) and Water Systems and Optimization (5 papers). Nauman Shahid is often cited by papers focused on Anomaly Detection Techniques and Applications (8 papers), Sparse and Compressive Sensing Techniques (7 papers) and Water Systems and Optimization (5 papers). Nauman Shahid collaborates with scholars based in Pakistan, Switzerland and Japan. Nauman Shahid's co-authors include Ijaz Haider Naqvi, Saad Qaisar, Pierre Vandergheynst, Vassilis Kalofolias, Nathanaël Perraudin, Gilles Puy, Michael M. Bronstein, Xavier Bresson, Nauman Ahmad Zaffar and Faisal Mahmood and has published in prestigious journals such as IEEE Signal Processing Letters, Artificial Intelligence Review and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Nauman Shahid

20 papers receiving 499 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nauman Shahid Pakistan 11 213 169 152 110 86 22 517
Lin Gao China 15 400 1.9× 259 1.5× 248 1.6× 107 1.0× 60 0.7× 83 835
Lin Zhou China 14 134 0.6× 219 1.3× 349 2.3× 69 0.6× 83 1.0× 70 716
Moon Kyou Song South Korea 13 151 0.7× 125 0.7× 88 0.6× 160 1.5× 66 0.8× 30 419
J.N. Driessen Netherlands 9 389 1.8× 92 0.5× 86 0.6× 82 0.7× 120 1.4× 17 590
E. Zervas Greece 12 212 1.0× 179 1.1× 168 1.1× 67 0.6× 66 0.8× 48 534
Chaoqun Yang China 15 215 1.0× 209 1.2× 227 1.5× 94 0.9× 197 2.3× 46 851
M.A. Masnadi-Shirazi Iran 9 131 0.6× 68 0.4× 61 0.4× 106 1.0× 70 0.8× 39 537
Jin Xie China 14 235 1.1× 141 0.8× 52 0.3× 155 1.4× 58 0.7× 42 610
Carsten Fritsche Sweden 14 319 1.5× 204 1.2× 512 3.4× 73 0.7× 38 0.4× 60 745

Countries citing papers authored by Nauman Shahid

Since Specialization
Citations

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

Fields of papers citing papers by Nauman Shahid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nauman Shahid

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

All Works

20 of 20 papers shown
1.
Rao, Xin, Qianyun Chen, Nauman Shahid, et al.. (2024). Application of dielectric properties for identification of normal and malignant gastrointestinal tumors and lymph nodes ex vivo. Physical and Engineering Sciences in Medicine. 48(1). 75–85.
2.
Shahid, Nauman & Anarta Ghosh. (2019). TrajecNets: Online Failure Evolution Analysis in 2D Space. International Journal of Prognostics and Health Management. 10(4). 7 indexed citations
3.
Shahid, Nauman, et al.. (2019). Tensor Robust PCA on Graphs. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 5406–5410. 3 indexed citations
4.
Mahmood, Faisal, Nauman Shahid, Ulf Skoglund, & Pierre Vandergheynst. (2018). Adaptive Graph-Based Total Variation for Tomographic Reconstructions. IEEE Signal Processing Letters. 25(5). 700–704. 29 indexed citations
5.
Shahid, Nauman. (2017). Scalable Low-rank Matrix and Tensor Decomposition on Graphs. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 indexed citations
6.
Shahid, Nauman, Nathanaël Perraudin, Vassilis Kalofolias, Benjamin Ricaud, & Pierre Vandergheynst. (2016). PCA using graph total variation. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 401. 4668–4672. 3 indexed citations
7.
Shahid, Nauman, Nathanaël Perraudin, Gilles Puy, & Pierre Vandergheynst. (2016). Compressive PCA for Low-Rank Matrices on Graphs. IEEE Transactions on Signal and Information Processing over Networks. 3(4). 695–710. 3 indexed citations
8.
Mahmood, Faisal, Nauman Shahid, Pierre Vandergheynst, & Ulf Skoglund. (2016). Graph-based sinogram denoising for tomographic reconstructions. PubMed. 2016. 3961–3964. 5 indexed citations
9.
Shahid, Nauman, Nathanaël Perraudin, Vassilis Kalofolias, Gilles Puy, & Pierre Vandergheynst. (2016). Fast Robust PCA on Graphs. IEEE Journal of Selected Topics in Signal Processing. 10(4). 740–756. 68 indexed citations
10.
Shahid, Nauman, Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, & Pierre Vandergheynst. (2015). Robust Principal Component Analysis on Graphs. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2812–2820. 67 indexed citations
11.
Shahid, Nauman, Ijaz Haider Naqvi, & Saad Qaisar. (2014). SVM Based Event Detection and Identification: Exploiting Temporal Attribute Correlations Using SensGru. Mathematical Problems in Engineering. 2014(1).
12.
Shahid, Nauman, et al.. (2014). Methodologies in power systems fault detection and diagnosis. Energy Systems. 6(1). 85–108. 61 indexed citations
13.
Shahid, Nauman, et al.. (2013). Joint event detection & identification: A clustering based approach for Wireless Sensor Networks. 249. 2333–2338. 5 indexed citations
14.
Shahid, Nauman, Ijaz Haider Naqvi, & Saad Qaisar. (2013). One-class support vector machines: analysis of outlier detection for wireless sensor networks in harsh environments. Artificial Intelligence Review. 43(4). 515–563. 50 indexed citations
15.
Shahid, Nauman, Ijaz Haider Naqvi, & Saad Qaisar. (2012). Real time energy efficient approach to Outlier & event detection in wireless sensor networks. 5. 162–166. 12 indexed citations
16.
Shahid, Nauman, et al.. (2012). Frequency synchronization algorithms for 802.11n based MIMO-OFDM systems: A performance analysis. 391–396. 1 indexed citations
17.
Shahid, Nauman, et al.. (2012). Classification of localization algorithms for wireless sensor network: A survey. 1–5. 52 indexed citations
18.
19.
Shahid, Nauman, Ijaz Haider Naqvi, & Saad Qaisar. (2012). Characteristics and classification of outlier detection techniques for wireless sensor networks in harsh environments: a survey. Artificial Intelligence Review. 43(2). 193–228. 73 indexed citations
20.
Shahid, Nauman & Ijaz Haider Naqvi. (2011). Energy efficient outlier detection in WSNs based on temporal and attribute correlations. 7. 1–6. 10 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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