Justin King

778 total citations
51 papers, 617 citations indexed

About

Justin King is a scholar working on Electrical and Electronic Engineering, Condensed Matter Physics and Information Systems. According to data from OpenAlex, Justin King has authored 51 papers receiving a total of 617 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Electrical and Electronic Engineering, 24 papers in Condensed Matter Physics and 4 papers in Information Systems. Recurrent topics in Justin King's work include Radio Frequency Integrated Circuit Design (33 papers), Advanced Power Amplifier Design (24 papers) and GaN-based semiconductor devices and materials (24 papers). Justin King is often cited by papers focused on Radio Frequency Integrated Circuit Design (33 papers), Advanced Power Amplifier Design (24 papers) and GaN-based semiconductor devices and materials (24 papers). Justin King collaborates with scholars based in Ireland, China and United States. Justin King's co-authors include Thomas J. Brazil, Jialin Cai, Lingling Sun, Chao Yu, Jun Liu, Shichang Chen, Kiran Lakkaraju, Adam Slagell, José C. Pedro and Alan Colman and has published in prestigious journals such as IEEE Access, IEEE Transactions on Microwave Theory and Techniques and Behavior Research Methods.

In The Last Decade

Justin King

47 papers receiving 604 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Justin King Ireland 12 493 264 50 45 32 51 617
E. Gebara United States 13 706 1.4× 230 0.9× 70 1.4× 23 0.5× 46 1.4× 81 794
Chiara Ramella Italy 14 459 0.9× 165 0.6× 28 0.6× 24 0.5× 13 0.4× 61 567
A. Raghavan United States 10 530 1.1× 70 0.3× 56 1.1× 27 0.6× 52 1.6× 28 625
Jeffrey S. Walling United States 18 1.3k 2.7× 83 0.3× 22 0.4× 10 0.2× 47 1.5× 75 1.4k
Hongtao Xu China 20 1.2k 2.3× 324 1.2× 83 1.7× 9 0.2× 18 0.6× 116 1.3k
Chaoliang Zhang Japan 10 308 0.6× 84 0.3× 14 0.3× 53 1.2× 19 0.6× 25 478
Takatsugu Ono Japan 9 115 0.2× 52 0.2× 54 1.1× 65 1.4× 38 1.2× 52 288
G. Leuzzi Italy 20 1.1k 2.3× 157 0.6× 71 1.4× 14 0.3× 47 1.5× 128 1.2k
Y. Campos‐Roca Spain 14 337 0.7× 65 0.2× 21 0.4× 115 2.6× 4 0.1× 53 663
Shouhei Kousai Japan 16 749 1.5× 37 0.1× 14 0.3× 48 1.1× 24 0.8× 37 779

Countries citing papers authored by Justin King

Since Specialization
Citations

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

Fields of papers citing papers by Justin King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Justin King

This figure shows the co-authorship network connecting the top 25 collaborators of Justin King. A scholar is included among the top collaborators of Justin King 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 Justin King. Justin King 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.
King, Justin & Gian Piero Gibiino. (2024). Research Activities From the MOMA Workshop [From the Guest Editor’s Desk]. IEEE Microwave Magazine. 26(1). 10–12.
2.
Miller, Nicholas C., Matt Grupen, Gian Piero Gibiino, & Justin King. (2023). Nonlinear RF Modeling of GaN HEMTs With Fermi Kinetics Transport and the ASM-HEMT Compact Model [Young Professionals]. IEEE Microwave Magazine. 25(1). 78–87. 1 indexed citations
3.
4.
Wang, Shijie, et al.. (2022). Memory polynomial based support vector regression dynamic behavioral model for Doherty power amplifiers. International Journal of Numerical Modelling Electronic Networks Devices and Fields. 35(4). 2 indexed citations
5.
King, Justin, et al.. (2021). Energy and Charge Conservation for FET Models. 1 indexed citations
6.
King, Justin, et al.. (2021). Design of a multi‐octave power amplifier using broadband load‐pull X‐parameters. International Journal of Numerical Modelling Electronic Networks Devices and Fields. 34(5). 7 indexed citations
7.
King, Justin. (2021). Efficientenergy‐conservativedispersive transistor modelling usingdiscrete‐timeconvolution and artificial neural networks. International Journal of Numerical Modelling Electronic Networks Devices and Fields. 34(5). 2 indexed citations
8.
Cai, Jialin, et al.. (2020). A Combined Broadband Model for GaN HEMTs in Admittance Domain Based on Canonical Piecewise Linear Functions. IEEE Transactions on Microwave Theory and Techniques. 68(12). 5042–5054. 11 indexed citations
9.
King, Justin, et al.. (2020). Large‐signal behavioral model for radio frequency power transistors based on modified canonical sectionwise piecewise‐linear functions. International Journal of Numerical Modelling Electronic Networks Devices and Fields. 33(6).
10.
Mani, Ganapathy, et al.. (2020). DeCrypto Pro: Deep Learning Based Cryptomining Malware Detection Using Performance Counters. 109–118. 11 indexed citations
11.
Cai, Jialin, Justin King, Chao Yu, et al.. (2019). Bayesian Inference-Based Behavioral Modeling Technique for GaN HEMTs. IEEE Transactions on Microwave Theory and Techniques. 67(6). 2291–2301. 35 indexed citations
12.
Cai, Jialin, Justin King, Chao Yu, Jun Liu, & Lingling Sun. (2018). Support Vector Regression-Based Behavioral Modeling Technique for RF Power Transistors. IEEE Microwave and Wireless Components Letters. 28(5). 428–430. 92 indexed citations
13.
Cai, Jialin, Chao Yu, Lingling Sun, Shichang Chen, & Justin King. (2018). Dynamic Behavioral Modeling of RF Power Amplifier Based on Time-Delay Support Vector Regression. IEEE Transactions on Microwave Theory and Techniques. 67(2). 533–543. 46 indexed citations
14.
King, Justin, et al.. (2018). Efficient Reconstruction Techniques for Disaster Recovery in Secret-Split Datastores. Digital Commons - Michigan Tech (Michigan Technological University). 2429. 66–78.
15.
King, Justin, et al.. (2018). Bayesian inference-based small-signal modeling technique for GaN HEMTs. International Journal of RF and Microwave Computer-Aided Engineering. 28(8). e21509–e21509. 12 indexed citations
16.
King, Justin, et al.. (2013). A simplified procedure for the design of continuous Class-F power amplifiers. European Microwave Conference. 1479–1482. 4 indexed citations
17.
King, Justin & Thomas J. Brazil. (2012). A GaN HEMT equivalent circuit model with novel approach to dispersion modelling. European Microwave Integrated Circuit Conference. 68–71. 3 indexed citations
18.
King, Justin & Thomas J. Brazil. (2012). Nonlinear Electrothermal GaN HEMT Model Applied to High-Efficiency Power Amplifier Design. IEEE Transactions on Microwave Theory and Techniques. 61(1). 444–454. 93 indexed citations
19.
King, Justin, Kiran Lakkaraju, & Adam Slagell. (2009). A taxonomy and adversarial model for attacks against network log anonymization. 1286–1293. 24 indexed citations
20.
King, Justin, et al.. (1980). A mutual inductance shocker. Behavior Research Methods. 12(6). 605–606. 29 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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