Junda Wu
Impact in
- Surfaces, Coatings and Films top 5%
- Surface Modification and Superhydrophobicity
- Water Science and Technology top 10%
- Membrane Separation Technologies
Papers in
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- Topic Modeling 4
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- Surface Modification and Superhydrophobicity 9
- Co-authors
- Jiangdong Dai (8 shared papers)Yongsheng Yan (6 shared papers)Chunxiang Li (5 shared papers)Atian Xie (2 shared papers)Jiuyun Cui (2 shared papers)Yunqi Wang (1 shared paper)Zhi Zhu (1 shared paper)Zhixiang Liu (1 shared paper)
- Journals
- Journal of Membrane Science (2 papers)New Journal of Chemistry (2 papers)Desalination (1 paper)Nature Communications (1 paper)Separation and Purification Technology (1 paper)
- Partner nations
- ChinaUnited StatesPoland
In The Last Decade
Junda Wu
24 papers receiving 275 citations
Peers
Comparison fields: 5 of 40
- Surfaces, Coatings and Films 112
- Water Science and Technology 105
- Renewable Energy, Sustainability and the Environment 67
- Biomaterials 40
- Management Science and Operations Research 24
Countries citing papers authored by Junda Wu
This map shows the geographic impact of Junda 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 Junda Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junda Wu more than expected).
Fields of papers citing papers by Junda Wu
This network shows the impact of papers produced by Junda 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 Junda Wu. The network helps show where Junda Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Junda 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 65 | |
| 2 | 2020 | 35 | |
| 3 | 2022 | 35 | |
| 4 | 2023 | 22 | |
| 5 | 2024 | 21 | |
| 6 | 2020 | 16 | |
| 7 | 2021 | 16 | |
| 8 | 2022 | 9 | |
| 9 | 2024 | 9 | |
| 10 | 2021 | 8 | |
| 11 | 2024 | 7 | |
| 12 | 2020 | 6 | |
| 13 | 2021 | 5 | |
| 14 | 2023 | 4 | |
| 15 | 2024 | 4 | |
| 16 | 2023 | 4 | |
| 17 | 2021 | 3 | |
| 18 | 2023 | 3 | |
| 19 | 2025 | 2 | |
| 20 | 2023 | 1 |
About Junda Wu
Junda Wu is a scholar working on Artificial Intelligence, Surfaces, Coatings and Films, Information Systems, Water Science and Technology and Management Science and Operations Research, having authored 29 papers that have together received 279 indexed citations. Recurring topics across this work include Surface Modification and Superhydrophobicity (9 papers), Recommender Systems and Techniques (8 papers), Advanced Bandit Algorithms Research (6 papers), Membrane Separation Technologies (6 papers), Topic Modeling (4 papers), Advanced Sensor and Energy Harvesting Materials (4 papers), Solar-Powered Water Purification Methods (3 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Surfaces, Coatings and Films (112 citations), Water Science and Technology (105 citations), Renewable Energy, Sustainability and the Environment (67 citations), Biomaterials (40 citations) and Management Science and Operations Research (24 citations). Junda Wu has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Jiangdong Dai, Yongsheng Yan, Chunxiang Li, Atian Xie, Jiuyun Cui, Yunqi Wang, Zhi Zhu, Zhixiang Liu, Yongsheng Yan and Jin Yang. Their work appears in journals such as Journal of Membrane Science, New Journal of Chemistry, Desalination, Nature Communications and Separation and Purification Technology.
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.