Hao Wu
Impact in
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- Context-Aware Activity Recognition Systems
- Human Pose and Action Recognition
- Information Systems top 0.5%
- Recommender Systems and Techniques
Papers in
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- Recommender Systems and Techniques 36
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- Topic Modeling 21
- Advanced Graph Neural Networks 17
- Co-authors
- Lei Zhang (44 shared papers)Kun Yue (17 shared papers)Jun He (11 shared papers)Aiguo Song (30 shared papers)Ching‐Hsien Hsu (7 shared papers)Yijian Pei (23 shared papers)Bo Li (13 shared papers)Xin Wang (15 shared papers)
- Journals
- Knowledge-Based Systems (10 papers)IEEE Sensors Journal (7 papers)IEEE Transactions on Instrumentation and Measurement (6 papers)IEEE Journal of Biomedical and Health Informatics (5 papers)Future Generation Computer Systems (5 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Hao Wu
147 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 118
- Computer Vision and Pattern Recognition 795
- Information Systems 867
- Computer Networks and Communications 772
- Artificial Intelligence 791
- Computational Mathematics 11
Countries citing papers authored by Hao Wu
This map shows the geographic impact of Hao Wu'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 Hao Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Wu more than expected).
Fields of papers citing papers by Hao Wu
This network shows the impact of papers produced by Hao Wu. 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 Hao Wu. The network helps show where Hao Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Hao Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 168 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 141 | |
| 2 | 2018 | 110 | |
| 3 | 2017 | 103 | |
| 4 | 2019 | 87 | |
| 5 | 2018 | 83 | |
| 6 | 2022 | 78 | |
| 7 | 2015 | 58 | |
| 8 | 2022 | 58 | |
| 9 | 2022 | 54 | |
| 10 | 2018 | 50 | |
| 11 | 2016 | 48 | |
| 12 | 2023 | 47 | |
| 13 | 2021 | 46 | |
| 14 | 2023 | 42 | |
| 15 | 2022 | 40 | |
| 16 | 2021 | 39 | |
| 17 | 2022 | 38 | |
| 18 | 2007 | 36 | |
| 19 | 2023 | 35 | |
| 20 | 2014 | 35 |
About Hao Wu
Hao Wu is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 168 papers that have together received 2.2k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (36 papers), Context-Aware Activity Recognition Systems (32 papers), Caching and Content Delivery (23 papers), IoT and Edge/Fog Computing (22 papers), Topic Modeling (21 papers), Advanced Graph Neural Networks (17 papers), Non-Invasive Vital Sign Monitoring (13 papers) and Human Pose and Action Recognition (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (795 citations), Information Systems (867 citations), Computer Networks and Communications (772 citations), Artificial Intelligence (791 citations) and Computational Mathematics (11 citations). Hao Wu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Lei Zhang, Kun Yue, Jun He, Aiguo Song, Ching‐Hsien Hsu, Yijian Pei, Bo Li, Xin Wang, Binbin Zhang and Wenbo Huang. Their work appears in journals such as Knowledge-Based Systems, IEEE Sensors Journal, IEEE Transactions on Instrumentation and Measurement, IEEE Journal of Biomedical and Health Informatics and Future Generation Computer 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.