Abigail Koay

472 citations
14 papers · 257 · h-index 7

Impact in

Papers in

Abigail Koay

13 papers receiving 244 citations

Peers

Abigail Koay
Comparison fields: 5 of 49
  • Health Informatics 11
  • Computer Networks and Communications 163
  • Signal Processing 73
  • Artificial Intelligence 101
  • Control and Systems Engineering 68
Replace Ahmad K. Al Hwaitat with:
Ahmad K. Al Hwaitat Jordan
Houda Jmila France
Zhiyi Tian Australia
Yin Minn Pa Pa Japan
Xixiang Lyu China
Xueluan Gong China
Santosh Kumar Sahu India
Jan Spooren Belgium
Amir Taherkordi Norway
Gonzalo De La Torre Parra United States
Abigail Koay relative to Ahmad K. Al Hwaitat Jordan Ahmad K. Al Hwaitat's profile →
Citations per field
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Ahmad K. Al Hwaitat · 1×
Citations per year

Countries citing papers authored by Abigail Koay

Since Specialization
Citations

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

Fields of papers citing papers by Abigail Koay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Abigail Koay, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Abigail Koay Line = papers co-authored together Abigail Koay links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 201867
2 202262
3 202444
4 201837
5 201918
6 20188
7 20217
8 20215
9 20252
10 20222
11 20192
12 20222
13 20251
14 20210

About Abigail Koay

Abigail Koay is a scholar working on Computer Networks and Communications, Signal Processing, Information Systems, Artificial Intelligence and Control and Systems Engineering, having authored 14 papers that have together received 257 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (6 papers), Advanced Malware Detection Techniques (4 papers), Smart Grid Security and Resilience (3 papers), Retinal Imaging and Analysis (2 papers), Cloud Computing and Resource Management (2 papers), IoT and Edge/Fog Computing (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers) and Glaucoma and retinal disorders (2 papers). The work is most often cited by research in Health Informatics (11 citations), Computer Networks and Communications (163 citations), Signal Processing (73 citations), Artificial Intelligence (101 citations) and Control and Systems Engineering (68 citations). Abigail Koay has collaborated with scholars based in New Zealand, Australia and Germany. Frequent co-authors include Ian Welch, Ryan K. L. Ko, Hinne Hettema, Kenneth Radke, Saad Qaisar, Winston K.G. Seah, Aaron Chen, Michael Mayo, Michael Gerndt and Panos Patros. Their work appears in journals such as Software Practice and Experience, IEEE Access, Journal of Intelligent Information Systems, Frontiers of Computer Science and Journal of Advanced Nursing.

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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