Edward Gan
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
- Data Management and Algorithms
- Time Series Analysis and Forecasting
- Artificial Intelligence top 10%
- Security and Verification in Computing
- Data Stream Mining Techniques
- Anomaly Detection Techniques and Applications
Papers in
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- Data Stream Mining Techniques 4
- Anomaly Detection Techniques and Applications 4
- Domain Adaptation and Few-Shot Learning 3
- Semantic Web and Ontologies 2
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- Data Management and Algorithms 4
- Time Series Analysis and Forecasting 4
- Advanced Malware Detection Techniques 2
- Co-authors
- Peter Bailis (12 shared papers)Joseph Tassarotti (2 shared papers)Gang Tan (2 shared papers)Greg Morrisett (2 shared papers)Jean-Baptiste Tristan (2 shared papers)Deepak Narayanan (2 shared papers)Samuel Madden (2 shared papers)Jialin Ding (2 shared papers)
- Journals
- Proceedings of the VLDB Endowment (4 papers)ACM SIGPLAN Notices (1 paper)ACM Transactions on Database Systems (1 paper)The VLDB Journal (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesUnited KingdomIsrael
In The Last Decade
Edward Gan
14 papers receiving 249 citations
Peers
Comparison fields: 5 of 41
- Signal Processing 100
- Artificial Intelligence 184
- Hardware and Architecture 35
- Computer Networks and Communications 93
- Software 15
Countries citing papers authored by Edward Gan
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
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 83 | |
| 2 | 2017 | 63 | |
| 3 | 2018 | 31 | |
| 4 | 2017 | 17 | |
| 5 | 2020 | 12 | |
| 6 | 2020 | 12 | |
| 7 | 2018 | 12 | |
| 8 | 2012 | 11 | |
| 9 | Prioritizing Attention in Analytic Monitoring. | 2017 | 4 |
| 10 | 2020 | 4 | |
| 11 | 2018 | 4 | |
| 12 | 2017 | 3 | |
| 13 | 2019 | 3 | |
| 14 | 2019 | 1 |
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 260 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (4 papers), Data Management and Algorithms (4 papers), Time Series Analysis and Forecasting (4 papers), Advanced Database Systems and Queries (4 papers), Anomaly Detection Techniques and Applications (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Semantic Web and Ontologies (2 papers) and Advanced Malware Detection Techniques (2 papers). The work is most often cited by research in Signal Processing (100 citations), Artificial Intelligence (184 citations), Hardware and Architecture (35 citations), Computer Networks and Communications (93 citations) and Software (15 citations). Edward Gan has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Peter Bailis, Joseph Tassarotti, Gang Tan, Greg Morrisett, Jean-Baptiste Tristan, Deepak Narayanan, Samuel Madden, Jialin Ding, Kai Sheng Tai and Matei Zaharia. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGPLAN Notices, ACM Transactions on Database Systems, The VLDB Journal 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.