Dejing Dou
- Artificial Intelligence top 1%
- Topic Modeling 18
- Advanced Graph Neural Networks 18
- Privacy-Preserving Technologies in Data 18
- Domain Adaptation and Few-Shot Learning 17
- Adversarial Robustness in Machine Learning 12
- Cryptography and Data Security 9
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- Advanced Neural Network Applications 15
- Health Informatics top 5%
- Media Technology top 5%
- Information Systems top 5%
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- Complex Network Analysis Techniques 10
- Co-authors
- Haoyi XiongXingjian LiJi LiuJavid EbrahimiNhatHai PhanJiang BianJingbo ZhouYue Wang
- Journals
- Machine Learning (5 papers)ACM Transactions on Knowledge Discovery from Data (5 papers)IEEE Internet of Things Journal (4 papers)
- Partner nations
- ChinaUnited StatesMacao
In The Last Decade
Dejing Dou
105 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 518
- Health Informatics 27
- Media Technology 98
- Information Systems 237
Countries citing papers authored by Dejing Dou
This map shows the geographic impact of Dejing Dou'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 Dejing Dou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dejing Dou more than expected).
Fields of papers citing papers by Dejing Dou
This network shows the impact of papers produced by Dejing Dou. 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 Dejing Dou. The network helps show where Dejing Dou may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dejing Dou, 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 | 2025 | 1 | |
| 2 | 2024 | 9 | |
| 3 | 2024 | 24 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 13 | |
| 6 | 2023 | 29 | |
| 7 | 2023 | 42 | |
| 8 | 2023 | 24 | |
| 9 | 2022 | 36 | |
| 10 | 2022 | 18 | |
| 11 | 2022 | 3 | |
| 12 | 2021 | 10 | |
| 13 | 2021 | 14 | |
| 14 | 2020 | 33 | |
| 15 | Pay Attention to Features, Transfer Learn faster CNNs | 2020 | 30 |
| 16 | 2020 | 7 | |
| 17 | Adversarial Attacks on Deep Graph Matching | 2020 | 13 |
| 18 | Preserving Differential Privacy in Adversarial Learning with Provable Robustness. | 2019 | 3 |
| 19 | 2017 | 19 | |
| 20 | A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets | 2016 | 20 |
About Dejing Dou
Dejing Dou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Issues, ethics and legal aspects and Transportation, having authored 109 papers that have together received 2.3k indexed citations. Recurring topics across this work include Topic Modeling (18 papers), Advanced Graph Neural Networks (18 papers), Privacy-Preserving Technologies in Data (18 papers), Domain Adaptation and Few-Shot Learning (17 papers), Advanced Neural Network Applications (15 papers), Adversarial Robustness in Machine Learning (12 papers), Complex Network Analysis Techniques (10 papers) and Cryptography and Data Security (9 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Computer Vision and Pattern Recognition (518 citations), Health Informatics (27 citations), Media Technology (98 citations) and Information Systems (237 citations). Dejing Dou has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Haoyi Xiong, Xingjian Li, Ji Liu, Javid Ebrahimi, NhatHai Phan, Jiang Bian, Jingbo Zhou, Yue Wang, Xintao Wu and Xuhong Li. Their work appears in journals such as Machine Learning, ACM Transactions on Knowledge Discovery from Data, IEEE Internet of Things Journal, Knowledge and Information Systems and IEEE Transactions on Multimedia.
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.