Anju P. Johnson

992 total citations
27 papers, 601 citations indexed

About

Anju P. Johnson is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Hardware and Architecture. According to data from OpenAlex, Anju P. Johnson has authored 27 papers receiving a total of 601 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Electrical and Electronic Engineering, 13 papers in Cellular and Molecular Neuroscience and 11 papers in Hardware and Architecture. Recurrent topics in Anju P. Johnson's work include Advanced Memory and Neural Computing (13 papers), Neuroscience and Neural Engineering (12 papers) and Physical Unclonable Functions (PUFs) and Hardware Security (10 papers). Anju P. Johnson is often cited by papers focused on Advanced Memory and Neural Computing (13 papers), Neuroscience and Neural Engineering (12 papers) and Physical Unclonable Functions (PUFs) and Hardware Security (10 papers). Anju P. Johnson collaborates with scholars based in United Kingdom, India and United States. Anju P. Johnson's co-authors include Rajat Subhra Chakraborty, Stephen Trimberger, J. Wong, Debdeep Mukhopadhyay, Liam McDaid, Junxiu Liu, Andy M. Tyrrell, David M. Halliday, Jim Harkin and Alan G. Millard and has published in prestigious journals such as IEEE Access, Sensors and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Anju P. Johnson

25 papers receiving 569 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anju P. Johnson United Kingdom 11 314 294 161 129 113 27 601
H. Ekin Sumbul United States 10 184 0.6× 346 1.2× 135 0.8× 118 0.9× 65 0.6× 24 522
Giuseppe Tagliavini Italy 18 386 1.2× 503 1.7× 217 1.3× 121 0.9× 41 0.4× 53 884
Michael Gautschi Switzerland 13 262 0.8× 441 1.5× 175 1.1× 81 0.6× 24 0.2× 24 630
Xuan‐Tu Tran Vietnam 12 205 0.7× 297 1.0× 189 1.2× 155 1.2× 29 0.3× 87 560
Megan Wachs United States 12 392 1.2× 295 1.0× 318 2.0× 66 0.5× 89 0.8× 17 827
Sai Rahul Chalamalasetti United States 10 202 0.6× 370 1.3× 178 1.1× 118 0.9× 48 0.4× 32 587
Francesca Palumbo Italy 12 268 0.9× 168 0.6× 157 1.0× 56 0.4× 35 0.3× 65 454
Éric Flamand Italy 13 417 1.3× 435 1.5× 330 2.0× 98 0.8× 24 0.2× 18 872
Joo-Young Kim South Korea 17 146 0.5× 620 2.1× 192 1.2× 176 1.4× 47 0.4× 80 940
Weixia Xu China 12 89 0.3× 221 0.8× 119 0.7× 141 1.1× 45 0.4× 68 439

Countries citing papers authored by Anju P. Johnson

Since Specialization
Citations

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

Fields of papers citing papers by Anju P. Johnson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anju P. Johnson. 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 Anju P. Johnson. The network helps show where Anju P. Johnson may publish in the future.

Co-authorship network of co-authors of Anju P. Johnson

This figure shows the co-authorship network connecting the top 25 collaborators of Anju P. Johnson. A scholar is included among the top collaborators of Anju P. Johnson 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 Anju P. Johnson. Anju P. Johnson 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.
2.
Johnson, Anju P., et al.. (2024). Robust Facial Emotion Detection in Low-Light Conditions: A Novel Approach Using Real-Time WebSocket Data Transfer. Huddersfield Research Portal (University of Huddersfield). 1–6.
3.
Hafeez, Maryam, et al.. (2023). LoRa-PUF: A Two-Step Security Solution for LoRaWAN. Huddersfield Research Portal (University of Huddersfield). 1–6. 4 indexed citations
4.
Holmes, Violeta, et al.. (2023). New Avenues for Automated Railway Safety Information Processing in Enterprise Architecture: An NLP Approach. IEEE Access. 11. 44413–44424. 3 indexed citations
5.
Johnson, Anju P., et al.. (2023). Predicting Drug Review Polarity Using the Combination Model of Multi-Sense Word Embedding and Fuzzy Latent Dirichlet Allocation (FLDA). IEEE Access. 11. 118538–118546. 4 indexed citations
6.
Johnson, Anju P., Hussain Al-Aqrabi, & Richard Hill. (2020). Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems. Sensors. 20(3). 844–844. 9 indexed citations
7.
Al-Aqrabi, Hussain, Anju P. Johnson, Richard Hill, P.M. Lane, & Tariq Alsboui. (2020). Hardware-Intrinsic Multi-Layer Security: A New Frontier for 5G Enabled IIoT. Sensors. 20(7). 1963–1963. 14 indexed citations
8.
Holmes, Violeta, et al.. (2020). Document Processing: Methods for Semantic Text Similarity Analysis. Huddersfield Research Portal (University of Huddersfield). 1–6. 32 indexed citations
9.
Liu, Junxiu, Liam McDaid, Alfonso Araque, et al.. (2019). GABA Regulation of Burst Firing in Hippocampal Astrocyte Neural Circuit: A Biophysical Model. Frontiers in Cellular Neuroscience. 13. 335–335. 7 indexed citations
10.
Johnson, Anju P., Junxiu Liu, Alan G. Millard, et al.. (2018). Time-multiplexed System-on-Chip using Fault-tolerant Astrocyte-Neuron Networks. 1076–1083. 5 indexed citations
11.
Johnson, Anju P., Junxiu Liu, Alan G. Millard, et al.. (2018). Fault-Tolerant Learning in Spiking Astrocyte-Neural Networks on FPGAs. Ulster University Research Portal (Ulster University). 5 indexed citations
12.
Harkin, Jim, Liam McDaid, Bryan Gardiner, et al.. (2018). FPGA-based Fault-injection and Data Acquisition of Self-repairing Spiking Neural Network Hardware. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 1–5. 4 indexed citations
13.
Liu, Junxiu, Jim Harkin, Liam McDaid, et al.. (2018). Bio-inspired Anomaly Detection for Low-cost Gas Sensors. 65. 1–4. 1 indexed citations
14.
Johnson, Anju P., Junxiu Liu, Alan G. Millard, et al.. (2017). Homeostatic Fault Tolerance in Spiking Neural Networks: A Dynamic Hardware Perspective. IEEE Transactions on Circuits and Systems I Regular Papers. 65(2). 687–699. 37 indexed citations
15.
Johnson, Anju P., et al.. (2016). An Improved DCM-Based Tunable True Random Number Generator for Xilinx FPGA. IEEE Transactions on Circuits & Systems II Express Briefs. 64(4). 452–456. 76 indexed citations
16.
Johnson, Anju P., David M. Halliday, Alan G. Millard, et al.. (2016). An FPGA-based hardware-efficient fault-tolerant astrocyte-neuron network. Ulster University Research Portal (Ulster University). 1–8. 17 indexed citations
17.
Johnson, Anju P., Sikhar Patranabis, Rajat Subhra Chakraborty, & Debdeep Mukhopadhyay. (2016). Remote Dynamic Clock Reconfiguration Based Attacks on Internet of Things Applications. 431–438. 4 indexed citations
18.
Johnson, Anju P., Rajat Subhra Chakraborty, & Debdeep Mukhopadhyay. (2015). A PUF-Enabled Secure Architecture for FPGA-Based IoT Applications. 1(2). 110–122. 56 indexed citations
19.
Johnson, Anju P., Sayandeep Saha, Rajat Subhra Chakraborty, Debdeep Mukhopadhyay, & Sezer Gören. (2014). Fault attack on AES via hardware Trojan insertion by dynamic partial reconfiguration of FPGA over ethernet. 1–8. 18 indexed citations
20.
Trimberger, Stephen, et al.. (2002). A time-multiplexed FPGA. 22–28. 220 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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