Zixiang Ding
Impact in
- Computational Mathematics top 10%
- Artificial Intelligence top 5%
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Advanced Text Analysis Techniques
- Machine Learning and ELM
Papers in
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- Machine Learning and ELM 7
- Sentiment Analysis and Opinion Mining 7
- Topic Modeling 7
- Domain Adaptation and Few-Shot Learning 6
- Advanced Text Analysis Techniques 6
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- Advanced Neural Network Applications 10
- Co-authors
- Rui Xia (6 shared papers)Dongbin Zhao (11 shared papers)Chengdong Li (4 shared papers)Jianqiang Yi (2 shared papers)Guiqing Zhang (2 shared papers)Jianfei Yu (3 shared papers)Mengran Zhang (2 shared papers)Yaran Chen (10 shared papers)
In The Last Decade
Zixiang Ding
26 papers receiving 817 citations
Peers
Comparison fields: 5 of 75
- Computational Mathematics 13
- Artificial Intelligence 449
- Building and Construction 172
- Computer Vision and Pattern Recognition 143
- Environmental Engineering 65
Countries citing papers authored by Zixiang Ding
This map shows the geographic impact of Zixiang Ding'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 Zixiang Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zixiang Ding more than expected).
Fields of papers citing papers by Zixiang Ding
This network shows the impact of papers produced by Zixiang Ding. 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 Zixiang Ding. The network helps show where Zixiang Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Zixiang Ding, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 231 | |
| 2 | 2020 | 83 | |
| 3 | 2019 | 76 | |
| 4 | 2019 | 60 | |
| 5 | 2018 | 54 | |
| 6 | 2021 | 54 | |
| 7 | 2020 | 51 | |
| 8 | 2018 | 30 | |
| 9 | 2021 | 29 | |
| 10 | 2023 | 28 | |
| 11 | 2022 | 26 | |
| 12 | 2023 | 19 | |
| 13 | 2022 | 19 | |
| 14 | 2018 | 11 | |
| 15 | 2023 | 10 | |
| 16 | 2023 | 8 | |
| 17 | 2022 | 7 | |
| 18 | 2023 | 6 | |
| 19 | 2020 | 6 | |
| 20 | 2017 | 5 |
About Zixiang Ding
Zixiang Ding is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Experimental and Cognitive Psychology and Building and Construction, having authored 27 papers that have together received 831 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (10 papers), Machine Learning and ELM (7 papers), Sentiment Analysis and Opinion Mining (7 papers), Topic Modeling (7 papers), Domain Adaptation and Few-Shot Learning (6 papers), Advanced Text Analysis Techniques (6 papers), Energy Load and Power Forecasting (3 papers) and Aluminum toxicity and tolerance in plants and animals (2 papers). The work is most often cited by research in Computational Mathematics (13 citations), Artificial Intelligence (449 citations), Building and Construction (172 citations), Computer Vision and Pattern Recognition (143 citations) and Environmental Engineering (65 citations). Zixiang Ding has collaborated with scholars based in China and Australia. Frequent co-authors include Rui Xia, Dongbin Zhao, Chengdong Li, Jianqiang Yi, Guiqing Zhang, Jianfei Yu, Mengran Zhang, Yaran Chen, Nannan Li and Huihui He. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Affective Computing, Energies and Ecotoxicology and Environmental Safety.
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.