Kam-Pui Chow

645 citations
61 papers · 495 · h-index 13

Impact in

Papers in

    • Digital and Cyber Forensics 26
    • Cybercrime and Law Enforcement Studies 8
    • Spam and Phishing Detection 7
    • Anomaly Detection Techniques and Applications 10
    • Internet Traffic Analysis and Secure E-voting 9

Kam-Pui Chow

55 papers receiving 470 citations

Peers

Kam-Pui Chow
Comparison fields: 5 of 82
  • Signal Processing 160
  • Information Systems 249
  • Artificial Intelligence 199
  • Computer Vision and Pattern Recognition 84
  • Hardware and Architecture 26
Replace Fareed Zaffar with:
Fareed Zaffar United States
Vincent H. Berk United States
Morteza Amini Iran
Shannon Bradshaw United States
Jean‐Charles Grégoire Canada
Manuel E. Correia Portugal
Paul Fodor United States
Praveen Rao United States
Zhidong Shen China
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Citations per field
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Citations per year

Countries citing papers authored by Kam-Pui Chow

Since Specialization
Citations

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

Fields of papers citing papers by Kam-Pui Chow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kam-Pui Chow. 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 Kam-Pui Chow. The network helps show where Kam-Pui Chow may publish in the future.

Co-authors

The 25 scholars most cited alongside Kam-Pui Chow, 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 Kam-Pui Chow Line = papers co-authored together Kam-Pui Chow links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199159
2 201046
3 201438
4 200828
5 201224
6 201119
7 201517
8 201717
9 201517
10 202116
11 198814
12 201414
13 201013
14 201611
15 201410
16 201810
17 201010
18 20129
19 20188
20 20107

About Kam-Pui Chow

Kam-Pui Chow is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 61 papers that have together received 495 indexed citations. Recurring topics across this work include Digital and Cyber Forensics (26 papers), Advanced Malware Detection Techniques (23 papers), Network Security and Intrusion Detection (13 papers), Anomaly Detection Techniques and Applications (10 papers), Internet Traffic Analysis and Secure E-voting (9 papers), Digital Media Forensic Detection (8 papers), Cybercrime and Law Enforcement Studies (8 papers) and Spam and Phishing Detection (7 papers). The work is most often cited by research in Signal Processing (160 citations), Information Systems (249 citations), Artificial Intelligence (199 citations), Computer Vision and Pattern Recognition (84 citations) and Hardware and Architecture (26 citations). Kam-Pui Chow has collaborated with scholars based in Hong Kong, China and United Kingdom. Frequent co-authors include Min Yang, Sujeet Shenoi, Richard E. Overill, Siu‐Ming Yiu, P D Weinstein, Anna George, Ann Logan, John J. Cebra, Yichen Wei and Jack R. Battisto. Their work appears in journals such as IFIP advances in information and communication technology, Infection and Immunity, Forensic Science International Digital Investigation, The Journal of Immunology and Applied Sciences.

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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