Safwan Wshah

865 total citations
41 papers, 547 citations indexed

About

Safwan Wshah is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Safwan Wshah has authored 41 papers receiving a total of 547 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 8 papers in Electrical and Electronic Engineering and 7 papers in Artificial Intelligence. Recurrent topics in Safwan Wshah's work include Advanced Neural Network Applications (7 papers), Power System Optimization and Stability (6 papers) and Handwritten Text Recognition Techniques (6 papers). Safwan Wshah is often cited by papers focused on Advanced Neural Network Applications (7 papers), Power System Optimization and Stability (6 papers) and Handwritten Text Recognition Techniques (6 papers). Safwan Wshah collaborates with scholars based in United States, Pakistan and Saudi Arabia. Safwan Wshah's co-authors include Venu Govindaraju, Gaurav Kumar, Xiaohan Zhang, Jianing Li, Jacob M. Remington, Waqas Sultani, Christian Skalka, Matthew Price, Zhixin Shi and Xingyu Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Child Psychology and Psychiatry.

In The Last Decade

Safwan Wshah

36 papers receiving 532 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Safwan Wshah United States 13 208 117 75 71 66 41 547
Rishav Singh India 12 165 0.8× 243 2.1× 56 0.7× 66 0.9× 8 0.1× 35 575
Hansung Lee South Korea 14 147 0.7× 145 1.2× 29 0.4× 39 0.5× 2 0.0× 48 681
Sudanthi Wijewickrema Australia 13 239 1.1× 266 2.3× 37 0.5× 25 0.4× 54 672
Dorothy Curtis United States 14 138 0.7× 131 1.1× 35 0.5× 527 7.4× 29 918
Filipe R. Cordeiro Brazil 13 156 0.8× 204 1.7× 28 0.4× 34 0.5× 51 515
Xinhang Song China 17 490 2.4× 174 1.5× 18 0.2× 13 0.2× 45 669
Shiyu Tang China 9 125 0.6× 120 1.0× 24 0.3× 23 0.3× 18 325
Carlos Figuera Spain 10 107 0.5× 33 0.3× 14 0.2× 166 2.3× 28 480
Mohammad Reza Yousefi Iran 13 149 0.7× 105 0.9× 8 0.1× 129 1.8× 53 467
Tiantian Liu China 9 111 0.5× 66 0.6× 7 0.1× 65 0.9× 20 525

Countries citing papers authored by Safwan Wshah

Since Specialization
Citations

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

Fields of papers citing papers by Safwan Wshah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Safwan Wshah

This figure shows the co-authorship network connecting the top 25 collaborators of Safwan Wshah. A scholar is included among the top collaborators of Safwan Wshah 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 Safwan Wshah. Safwan Wshah 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.
Potter, Alexandra, et al.. (2025). Machine learning prediction of conduct problems in children using the longitudinal ABCD study. Journal of Child Psychology and Psychiatry. 67(3). 390–399.
2.
Zhang, Xiaohan, et al.. (2025). Cross-View Meets Diffusion: Aerial Image Synthesis with Geometry and Text Guidance. 5356–5366. 3 indexed citations
3.
4.
Zhang, Xiaohan, et al.. (2024). Fine-Grained Permeable Surface Mapping through Parallel U-Net. Sensors. 24(7). 2134–2134.
5.
Zhang, Xiaohan, Xingyu Li, Waqas Sultani, Chen Chen, & Safwan Wshah. (2024). GeoDTR+: Toward Generic Cross-View Geolocalization via Geometric Disentanglement. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(12). 10419–10433. 8 indexed citations
6.
Zhang, Xiaohan, Xingyu Li, Waqas Sultani, Yi Zhou, & Safwan Wshah. (2023). Cross-View Geo-Localization via Learning Disentangled Geometric Layout Correspondence. Proceedings of the AAAI Conference on Artificial Intelligence. 37(3). 3480–3488. 33 indexed citations
7.
Wilson, Daniel H., Xiaohan Zhang, Waqas Sultani, & Safwan Wshah. (2023). Image and Object Geo-Localization. International Journal of Computer Vision. 132(4). 1350–1392. 12 indexed citations
8.
Wshah, Safwan, et al.. (2023). Detection and mitigation of GPS Spoofing Attacks on Phasor Measurement Units using deep learning. International Journal of Electrical Power & Energy Systems. 151. 109160–109160. 20 indexed citations
9.
Wshah, Safwan, et al.. (2022). Transformer-based deep learning model for forced oscillation localization. International Journal of Electrical Power & Energy Systems. 146. 108805–108805. 20 indexed citations
10.
Wshah, Safwan, et al.. (2022). Classification of clinically relevant intravascular volume status using point of care ultrasound and machine learning. Journal of Medical Imaging. 9(5). 54502–54502.
11.
Wshah, Safwan, et al.. (2021). Accurate Detection of False Data Injection Attacks in Renewable Power Systems Using Deep Learning. IEEE Access. 9. 135774–135789. 22 indexed citations
12.
Bates, Jason H. T., et al.. (2020). Classification and Detection of Breathing Patterns with Wearable Sensors and Deep Learning. Sensors. 20(22). 6481–6481. 31 indexed citations
13.
Bonnell, Levi N., Benjamin Littenberg, Safwan Wshah, & Gail L. Rose. (2020). A Machine Learning Approach to Identification of Unhealthy Drinking. The Journal of the American Board of Family Medicine. 33(3). 397–406. 17 indexed citations
14.
Hahn, Sage, et al.. (2020). Machine deep learning accurately detects endoleak after endovascular abdominal aortic aneurysm repair. SHILAP Revista de lepidopterología. 1. 5–12. 27 indexed citations
15.
Wshah, Safwan, Christian Skalka, & Matthew Price. (2019). Predicting Posttraumatic Stress Disorder Risk: A Machine Learning Approach. JMIR Mental Health. 6(7). e13946–e13946. 35 indexed citations
16.
Hahn, Sage, Christopher S. Morris, Daniel J. Bertges, & Safwan Wshah. (2019). Deep Learning for Recognition of Endoleak After Endovascular Abdominal Aortic Aneurysm Repair. 759–763. 7 indexed citations
17.
Hahn, Sage, et al.. (2019). SS26. Machine Deep Learning Accurately Detects Endoleak After Endovascular Abdominal Aortic Aneurysm Repair. Journal of Vascular Surgery. 69(6). e202–e203. 1 indexed citations
18.
Alshaabi, Thayer, et al.. (2019). ARTS: Automotive Repository of Traffic Signs for the United States. IEEE Transactions on Intelligent Transportation Systems. 22(1). 457–465. 12 indexed citations
19.
Wshah, Safwan, et al.. (2013). Segmentation-free keyword spotting framework using dynamic background model. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8658. 86580H–86580H. 5 indexed citations
20.
Wshah, Safwan, et al.. (2010). A Novel Lexicon Reduction Method for Arabic Handwriting Recognition. 22. 2865–2868. 17 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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