Edward Gan

447 citations
14 papers · 264 · h-index 8

Impact in

    • Advanced Malware Detection Techniques
    • Data Management and Algorithms
    • Security and Verification in Computing
    • Data Stream Mining Techniques
    • Anomaly Detection Techniques and Applications

Papers in

    • Data Stream Mining Techniques 4
    • Anomaly Detection Techniques and Applications 4
    • Domain Adaptation and Few-Shot Learning 3
    • Topic Modeling 2
    • Data Management and Algorithms 4
    • Time Series Analysis and Forecasting 4

Edward Gan

14 papers receiving 254 citations

Peers

Edward Gan
Comparison fields: 5 of 41
  • Signal Processing 101
  • Artificial Intelligence 186
  • Hardware and Architecture 36
  • Computer Networks and Communications 94
  • Software 15
Replace Caroline Trippel with:
Caroline Trippel United States
Alexandros Koliousis United Kingdom
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Pubali Datta United States
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Citations per field
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Citations per year

Countries citing papers authored by Edward Gan

Since Specialization
Citations

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

Fields of papers citing papers by Edward Gan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Edward Gan, 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 Edward Gan Line = papers co-authored together Edward Gan links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 201283
2 201764
3 201833
4 201717
5 202013
6 201812
7 202012
8 201211
9 20184
10 20204
11
Prioritizing Attention in Analytic Monitoring.
20174
12 20193
13 20173
14 20191

About Edward Gan

Edward Gan is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 14 papers that have together received 264 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (4 papers), Data Stream Mining Techniques (4 papers), Anomaly Detection Techniques and Applications (4 papers), Data Management and Algorithms (4 papers), Time Series Analysis and Forecasting (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Multimodal Machine Learning Applications (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Signal Processing (101 citations), Artificial Intelligence (186 citations), Hardware and Architecture (36 citations), Computer Networks and Communications (94 citations) and Software (15 citations). Edward Gan has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Peter Bailis, Joseph Tassarotti, Greg Morrisett, Gang Tan, Jean-Baptiste Tristan, Samuel Madden, Deepak Narayanan, Jialin Ding, Kai Sheng Tai and Matei Zaharia. Their work appears in journals such as Proceedings of the VLDB Endowment, The VLDB Journal, ACM SIGPLAN Notices, ACM Transactions on Database Systems and arXiv (Cornell University).

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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