Haicheng Tao
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- Complex Network Analysis Techniques 8
- Opinion Dynamics and Social Influence 4
- Artificial Intelligence top 10%
- Anomaly Detection Techniques and Applications 6
- Advanced Graph Neural Networks 5
- Sentiment Analysis and Opinion Mining 2
- Information Systems top 10%
- Recommender Systems and Techniques 4
- Spam and Phishing Detection 3
- Signal Processing top 10%
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- Network Security and Intrusion Detection 7
- Co-authors
- Jie CaoZhan BuXingquan ZhuYouquan WangWeichao LiangHui‐Jia LiGuixiang ZhuLei Chen
- Cited by
- Statistical and Nonlinear PhysicsArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- Expert Systems with Applications (1 paper)IEEE Transactions on Industrial Informatics (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Haicheng Tao
24 papers receiving 414 citations
Peers
Comparison fields: 5 of 77
- Statistical and Nonlinear Physics 105
- Artificial Intelligence 182
- Computer Vision and Pattern Recognition 111
- Information Systems 98
- Signal Processing 46
Countries citing papers authored by Haicheng Tao
This map shows the geographic impact of Haicheng Tao'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 Haicheng Tao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haicheng Tao more than expected).
Fields of papers citing papers by Haicheng Tao
This network shows the impact of papers produced by Haicheng Tao. 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 Haicheng Tao. The network helps show where Haicheng Tao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Haicheng Tao, 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 | 1 | |
| 2 | 2023 | 6 | |
| 3 | 2023 | 9 | |
| 4 | 2023 | 0 | |
| 5 | 2023 | 37 | |
| 6 | 2022 | 24 | |
| 7 | 2022 | 13 | |
| 8 | 2022 | 1 | |
| 9 | 2022 | 3 | |
| 10 | 2022 | 9 | |
| 11 | 2021 | 10 | |
| 12 | 2021 | 22 | |
| 13 | 2021 | 14 | |
| 14 | 2020 | 19 | |
| 15 | 2020 | 76 | |
| 16 | 2019 | 6 | |
| 17 | 2017 | 58 | |
| 18 | 2016 | 59 | |
| 19 | 2014 | 3 | |
| 20 | 2013 | 4 |
About Haicheng Tao
Haicheng Tao is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Computer Networks and Communications, having authored 27 papers that have together received 428 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (8 papers), Network Security and Intrusion Detection (7 papers), Anomaly Detection Techniques and Applications (6 papers), Advanced Graph Neural Networks (5 papers), Recommender Systems and Techniques (4 papers), Opinion Dynamics and Social Influence (4 papers), Spam and Phishing Detection (3 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (105 citations), Artificial Intelligence (182 citations) and Computer Vision and Pattern Recognition (111 citations). Haicheng Tao has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jie Cao, Zhan Bu, Xingquan Zhu, Youquan Wang, Weichao Liang, Hui‐Jia Li, Guixiang Zhu, Lei Chen, Jia Wu and Jianshan Sun. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Industrial Informatics and IEEE Transactions on Neural Networks and Learning Systems.
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.