V. Devabhaktuni

2.6k total citations · 1 hit paper
67 papers, 1.9k citations indexed

About

V. Devabhaktuni is a scholar working on Electrical and Electronic Engineering, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, V. Devabhaktuni has authored 67 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Electrical and Electronic Engineering, 20 papers in Aerospace Engineering and 14 papers in Artificial Intelligence. Recurrent topics in V. Devabhaktuni's work include Microwave Engineering and Waveguides (24 papers), Electromagnetic Simulation and Numerical Methods (11 papers) and Soil Moisture and Remote Sensing (10 papers). V. Devabhaktuni is often cited by papers focused on Microwave Engineering and Waveguides (24 papers), Electromagnetic Simulation and Numerical Methods (11 papers) and Soil Moisture and Remote Sensing (10 papers). V. Devabhaktuni collaborates with scholars based in United States, Canada and United Kingdom. V. Devabhaktuni's co-authors include Qi‐Jun Zhang, K.C. Gupta, M.C.E. Yagoub, Jianjun Xu, Naima Kaabouch, Hu Wen, Mohsen Riahi Manesh, Qijun Zhang, Sidike Paheding and Q.J. Zhang and has published in prestigious journals such as Journal of Hazardous Materials, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

V. Devabhaktuni

65 papers receiving 1.8k 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.

Artificial neural networks for rf and microwave design-from theory to practice

2003 542 citations Qi‐Jun Zhang, K.C. Gupta et al. IEEE Transactions on Microwave Theory and Techniques profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
V. Devabhaktuni United States	18	1.3k	454	260	175	98	67	1.9k
Feng Feng China	26	1.9k 1.4×	765 1.7×	183 0.7×	183 1.0×	132 1.3×	190	2.7k
Pavlos I. Lazaridis United Kingdom	27	1.5k 1.1×	862 1.9×	194 0.7×	125 0.7×	93 0.9×	206	2.2k
Ningfei Wang China	31	635 0.5×	1.6k 3.5×	221 0.8×	178 1.0×	74 0.8×	274	3.3k
Jianjun Xu China	21	1.2k 0.9×	98 0.2×	238 0.9×	118 0.7×	77 0.8×	108	1.9k
Riccardo E. Zich Italy	21	938 0.7×	691 1.5×	338 1.3×	50 0.3×	134 1.4×	211	1.7k
Flavio Canavero Italy	27	2.3k 1.8×	190 0.4×	87 0.3×	259 1.5×	118 1.2×	262	3.3k
Y. Rahmat–Samii United States	18	496 0.4×	767 1.7×	136 0.5×	79 0.5×	159 1.6×	80	1.1k
Wei Shao China	27	1.9k 1.4×	1.4k 3.1×	210 0.8×	243 1.4×	290 3.0×	177	2.6k
Qiqi Wang United States	24	283 0.2×	378 0.8×	172 0.7×	121 0.7×	52 0.5×	117	1.8k

Countries citing papers authored by V. Devabhaktuni

Since Specialization

Citations

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

Fields of papers citing papers by V. Devabhaktuni

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of V. Devabhaktuni

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Khoei, Tala Talaei, Khair Al Shamaileh, V. Devabhaktuni, & Naima Kaabouch. (2025). Performance analysis of capsule networks for detecting GPS spoofing attacks on unmanned aerial vehicles. International Journal of Information Security. 24(1).

Khoei, Tala Talaei, Hadjar Ould Slimane, Khair Al Shamaileh, V. Devabhaktuni, & Naima Kaabouch. (2024). Detecting Injection Attacks in ADS-B Devices Using RNN-Based Models. 1–8. 1 indexed citations

McCormick, Matthew, et al.. (2024). Classification and Source Location Indication of Jamming Attacks Targeting UAVs via Multi-output Multiclass Machine Learning Modeling. 1–5. 3 indexed citations

Paheding, Sidike, et al.. (2024). Cross-View Geo-Localization: A Survey. IEEE Access. 12. 192028–192050. 4 indexed citations

Khoei, Tala Talaei, et al.. (2023). Supervised Deep Learning Models for Detecting GPS Spoofing Attacks on Unmanned Aerial Vehicles. 340–346. 6 indexed citations

Slimane, Hadjar Ould, et al.. (2022). ADS-B Message Injection Attack on UAVs: Assessment of SVM-based Detection Techniques. 405–410. 9 indexed citations

Khoei, Tala Talaei, et al.. (2022). A Comparative Analysis of Supervised and Unsupervised Models for Detecting GPS Spoofing Attack on UAVs. 279–284. 23 indexed citations

Siddique, Nahian, Sidike Paheding, Md Zahangir Alom, & V. Devabhaktuni. (2021). Recurrent residual U-Net with EfficientNet encoder for medical image segmentation. Digital Commons - Michigan Tech (Michigan Technological University). 19–19. 10 indexed citations

Paheding, Sidike, et al.. (2021). Trends in Deep Learning for Medical Hyperspectral Image Analysis. IEEE Access. 9. 79534–79548. 55 indexed citations

10.

Caroff, Philippe, Paul R. Young, Vlad Stolojan, et al.. (2018). Solution‐Processed InAs Nanowire Transistors as Microwave Switches. Advanced Electronic Materials. 5(1). 6 indexed citations

11.

Manivannan, K., et al.. (2012). Particulate matter characterization by gray level co-occurrence matrix based support vector machines. Journal of Hazardous Materials. 223-224. 94–103. 45 indexed citations

12.

Bhatt, Deepak L., Priyanka Aggarwal, Paritosh Bhattacharya, & V. Devabhaktuni. (2011). GPS/INS Integration for Land Vehicle Navigation Using Source Difference Method. 1811–1817. 2 indexed citations

13.

Ahmad, M. Omair, et al.. (2011). Identification of CpG islands in DNA sequences using matched filters. PubMed. 2011. 6029–6032. 2 indexed citations

14.

Devabhaktuni, V., et al.. (2010). A new approach to simulate characterization of particulate matter employing support vector machines. Journal of Hazardous Materials. 186(2-3). 1254–1262. 13 indexed citations

15.

Devabhaktuni, V., et al.. (2009). Microarray image segmentation using chan-vese active contour model and level set method. PubMed. 2009. 3629–3632. 6 indexed citations

16.

Devabhaktuni, V., et al.. (2009). A New Approach to Analysis and Modeling of Esophageal Manometry Data in Humans. IEEE Transactions on Biomedical Engineering. 56(7). 1821–1830. 5 indexed citations

17.

Zhang, Qi‐Jun, K.C. Gupta, & V. Devabhaktuni. (2003). Artificial neural networks for rf and microwave design-from theory to practice. IEEE Transactions on Microwave Theory and Techniques. 51(4). 1339–1350. 542 indexed citations breakdown →

18.

Cao, Yi, et al.. (2003). An adjoint dynamic neural network technique for exact sensitivities in nonlinear transient modeling and high-speed interconnect design. 1. 165–168. 15 indexed citations

19.

Devabhaktuni, V., et al.. (2003). Advanced microwave modeling framework exploiting automatic model generation, knowledge neural networks, and space mapping. IEEE Transactions on Microwave Theory and Techniques. 51(7). 1822–1833. 134 indexed citations

20.

Devabhaktuni, V., et al.. (1998). A Neural Network Approach to the Modeling of Heterojunction Bipolar Transistors from S-Parameter Data. 306–311. 22 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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