Kaize Ding
Impact in
- Artificial Intelligence top 1%
- Advanced Graph Neural Networks
- Topic Modeling
- Anomaly Detection Techniques and Applications
- Domain Adaptation and Few-Shot Learning
- Information Systems top 2%
- Recommender Systems and Techniques
Papers in
-
- Advanced Graph Neural Networks 31
- Topic Modeling 15
- Domain Adaptation and Few-Shot Learning 13
- Anomaly Detection Techniques and Applications 11
- Text and Document Classification Technologies 6
-
- Recommender Systems and Techniques 7
- Co-authors
- Huan Liu (30 shared papers)Jundong Li (13 shared papers)Jianling Wang (7 shared papers)Hanghang Tong (6 shared papers)James Caverlee (4 shared papers)Liangjie Hong (1 shared paper)Zhe Xu (3 shared papers)Kai Shu (5 shared papers)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (2 papers)Scientific Reports (1 paper)Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (1 paper)Information Fusion (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Kaize Ding
48 papers receiving 1.1k citations
Kaize Ding's Hit Papers
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 924
- Information Systems 335
- Statistical and Nonlinear Physics 173
- Computer Networks and Communications 201
- Computer Vision and Pattern Recognition 134
Countries citing papers authored by Kaize Ding
This map shows the geographic impact of Kaize 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 Kaize Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaize Ding more than expected).
Fields of papers citing papers by Kaize Ding
This network shows the impact of papers produced by Kaize 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 Kaize Ding. The network helps show where Kaize Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Kaize 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 168 | |
| 2 | 2020 | 128 | |
| 3 | Data Augmentation for Deep Graph Learning Hit paper breakdown → | 2022 | 128 |
| 4 | 2020 | 99 | |
| 5 | 2019 | 94 | |
| 6 | 2021 | 74 | |
| 7 | 2020 | 47 | |
| 8 | 2020 | 45 | |
| 9 | 2022 | 34 | |
| 10 | 2021 | 32 | |
| 11 | 2021 | 30 | |
| 12 | 2023 | 24 | |
| 13 | 2022 | 24 | |
| 14 | 2022 | 20 | |
| 15 | 2023 | 17 | |
| 16 | 2023 | 16 | |
| 17 | 2022 | 16 | |
| 18 | 2020 | 16 | |
| 19 | 2022 | 15 | |
| 20 | 2021 | 15 |
About Kaize Ding
Kaize Ding is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research and Computer Networks and Communications, having authored 56 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (31 papers), Topic Modeling (15 papers), Domain Adaptation and Few-Shot Learning (13 papers), Anomaly Detection Techniques and Applications (11 papers), Recommender Systems and Techniques (7 papers), Text and Document Classification Technologies (6 papers), Multimodal Machine Learning Applications (5 papers) and Complex Network Analysis Techniques (5 papers). The work is most often cited by research in Artificial Intelligence (924 citations), Information Systems (335 citations), Statistical and Nonlinear Physics (173 citations), Computer Networks and Communications (201 citations) and Computer Vision and Pattern Recognition (134 citations). Kaize Ding has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Huan Liu, Jundong Li, Jianling Wang, Hanghang Tong, James Caverlee, Liangjie Hong, Zhe Xu, Kai Shu, Dingcheng Li and Tahora H. Nazer. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Scientific Reports, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Information Fusion and ACM Transactions on Knowledge Discovery from Data.
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.