Alexander Zhou
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Artificial Intelligence top 5%
- Privacy-Preserving Technologies in Data
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
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- Complex Network Analysis Techniques 8
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- Graph Theory and Algorithms 4
- Co-authors
- Hongzhi Yin (4 shared papers)Tong Chen (3 shared papers)Qinyong Wang (2 shared papers)Quoc Viet Hung Nguyen (2 shared papers)Lei Guo (1 shared paper)Lei Chen (8 shared papers)Junliang Yu (1 shared paper)Xiangliang Zhang (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (6 papers)The VLDB Journal (2 papers)ACM Transactions on Information Systems (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)2022 IEEE 38th International Conference on Data Engineering (ICDE) (1 paper)
In The Last Decade
Alexander Zhou
11 papers receiving 354 citations
Peers
Comparison fields: 5 of 43
- Information Systems 224
- Artificial Intelligence 247
- Statistical and Nonlinear Physics 52
- Signal Processing 42
- Computer Vision and Pattern Recognition 63
Countries citing papers authored by Alexander Zhou
This map shows the geographic impact of Alexander Zhou'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 Alexander Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Zhou more than expected).
Fields of papers citing papers by Alexander Zhou
This network shows the impact of papers produced by Alexander Zhou. 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 Alexander Zhou. The network helps show where Alexander Zhou may publish in the future.
Co-authors
The 24 scholars most cited alongside Alexander Zhou, 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 | 2019 | 122 | |
| 2 | 2021 | 78 | |
| 3 | 2022 | 65 | |
| 4 | 2022 | 24 | |
| 5 | 2021 | 21 | |
| 6 | 2020 | 15 | |
| 7 | 2022 | 14 | |
| 8 | 2022 | 9 | |
| 9 | 2023 | 8 | |
| 10 | 2023 | 2 | |
| 11 | 2023 | 1 | |
| 12 | 2024 | 0 | |
| 13 | 2024 | 0 |
About Alexander Zhou
Alexander Zhou is a scholar working on Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications and Information Systems, having authored 13 papers that have together received 359 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (8 papers), Graph Theory and Algorithms (4 papers), Data Management and Algorithms (3 papers), Caching and Content Delivery (3 papers), Advanced Graph Neural Networks (3 papers), Recommender Systems and Techniques (3 papers), Advanced Graph Theory Research (3 papers) and Privacy-Preserving Technologies in Data (2 papers). The work is most often cited by research in Information Systems (224 citations), Artificial Intelligence (247 citations), Statistical and Nonlinear Physics (52 citations), Signal Processing (42 citations) and Computer Vision and Pattern Recognition (63 citations). Alexander Zhou has collaborated with scholars based in Hong Kong, Australia and China. Frequent co-authors include Hongzhi Yin, Tong Chen, Qinyong Wang, Quoc Viet Hung Nguyen, Lei Guo, Lei Chen, Junliang Yu, Xiangliang Zhang, Kai Zheng and Mubashir Imran. Their work appears in journals such as Proceedings of the VLDB Endowment, The VLDB Journal, ACM Transactions on Information Systems, IEEE Transactions on Knowledge and Data Engineering and 2022 IEEE 38th International Conference on Data Engineering (ICDE).
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.