Dan Pei
- Computer Networks and Communications top 0.1%
- Network Security and Intrusion Detection 79
- Software System Performance and Reliability 77
- Network Traffic and Congestion Control 36
- Software-Defined Networks and 5G 30
- Artificial Intelligence top 0.2%
- Anomaly Detection Techniques and Applications 56
- Internet Traffic Analysis and Secure E-voting 26
- Signal Processing top 0.5%
- Time Series Analysis and Forecasting 20
- Software top 1%
- Hardware and Architecture top 2%
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- Cloud Computing and Resource Management 21
- Co-authors
- Youjian ZhaoYa SuShenglin ZhangLixia ZhangRong LiuChenhao NiuWei SunBeichuan Zhang
- Journals
- IEEE Transactions on Services Computing (6 papers)IEEE/ACM Transactions on Networking (5 papers)ACM SIGMETRICS Performance Evaluation Review (4 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Dan Pei
193 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Computer Networks and Communications 5.0k
- Artificial Intelligence 3.4k
- Signal Processing 1.0k
- Software 343
- Hardware and Architecture 369
Countries citing papers authored by Dan Pei
This map shows the geographic impact of Dan Pei'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 Dan Pei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Pei more than expected).
Fields of papers citing papers by Dan Pei
This network shows the impact of papers produced by Dan Pei. 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 Dan Pei. The network helps show where Dan Pei may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dan Pei, 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 | 2025 | 7 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 9 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 2 | |
| 10 | 2024 | 4 | |
| 11 | 2024 | 2 | |
| 12 | 2023 | 12 | |
| 13 | 2023 | 0 | |
| 14 | 2023 | 33 | |
| 15 | 2023 | 16 | |
| 16 | 2022 | 26 | |
| 17 | 2021 | 30 | |
| 18 | 2019 | 6 | |
| 19 | 2019 | 87 | |
| 20 | 2017 | 6 |
About Dan Pei
Dan Pei is a scholar working on Computer Networks and Communications, Software and Artificial Intelligence, having authored 212 papers that have together received 6.1k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (79 papers), Software System Performance and Reliability (77 papers), Anomaly Detection Techniques and Applications (56 papers), Network Traffic and Congestion Control (36 papers), Software-Defined Networks and 5G (30 papers), Internet Traffic Analysis and Secure E-voting (26 papers), Cloud Computing and Resource Management (21 papers) and Time Series Analysis and Forecasting (20 papers). The work is most often cited by research in Computer Networks and Communications (5.0k citations), Artificial Intelligence (3.4k citations) and Signal Processing (1.0k citations). Dan Pei has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Youjian Zhao, Ya Su, Shenglin Zhang, Lixia Zhang, Rong Liu, Chenhao Niu, Wei Sun, Beichuan Zhang, Dan Massey and Weibin Meng. Their work appears in journals such as IEEE Transactions on Services Computing, IEEE/ACM Transactions on Networking, ACM SIGMETRICS Performance Evaluation Review, IEEE Transactions on Network and Service Management and Computer Networks.
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.