Chaochao Chen
- Automotive Engineering top 1%
- Information Systems top 0.5%
- Recommender Systems and Techniques 62
- Artificial Intelligence top 0.5%
- Advanced Graph Neural Networks 36
- Privacy-Preserving Technologies in Data 28
- Topic Modeling 16
- Domain Adaptation and Few-Shot Learning 11
- Stochastic Gradient Optimization Techniques 10
- Computational Mathematics top 5%
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- Caching and Content Delivery 10
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- Advanced Bandit Algorithms Research 10
- Co-authors
- Michael PechtXiaolin ZhengNicholas WilliardGeorge VachtsevanosYan WangWei HeMarcos E. OrchardJun Zhou
- Journals
- Expert Systems with Applications (5 papers)IEEE Transactions on Knowledge and Data Engineering (5 papers)Knowledge-Based Systems (4 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Chaochao Chen
148 papers receiving 4.1k citations
Hit Papers
Peers
Comparison fields: 5 of 161
- Automotive Engineering 807
- Information Systems 1.4k
- Artificial Intelligence 1.8k
- Computational Mathematics 20
- Control and Systems Engineering 733
Countries citing papers authored by Chaochao Chen
This map shows the geographic impact of Chaochao Chen'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 Chaochao Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaochao Chen more than expected).
Fields of papers citing papers by Chaochao Chen
This network shows the impact of papers produced by Chaochao Chen. 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 Chaochao Chen. The network helps show where Chaochao Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chaochao Chen, 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 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 5 | |
| 11 | 2024 | 8 | |
| 12 | 2023 | 18 | |
| 13 | 2023 | 14 | |
| 14 | 2023 | 22 | |
| 15 | 2023 | 9 | |
| 16 | 2023 | 6 | |
| 17 | 2022 | 12 | |
| 18 | 2021 | 46 | |
| 19 | 2021 | 16 | |
| 20 | 2020 | 53 |
About Chaochao Chen
Chaochao Chen is a scholar working on Information Systems, Artificial Intelligence, Computational Mathematics, Transportation and Computer Vision and Pattern Recognition, having authored 170 papers that have together received 4.2k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (62 papers), Advanced Graph Neural Networks (36 papers), Privacy-Preserving Technologies in Data (28 papers), Topic Modeling (16 papers), Domain Adaptation and Few-Shot Learning (11 papers), Caching and Content Delivery (10 papers), Stochastic Gradient Optimization Techniques (10 papers) and Advanced Bandit Algorithms Research (10 papers). The work is most often cited by research in Automotive Engineering (807 citations), Information Systems (1.4k citations), Artificial Intelligence (1.8k citations), Computational Mathematics (20 citations) and Control and Systems Engineering (733 citations). Chaochao Chen has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Michael Pecht, Xiaolin Zheng, Nicholas Williard, George Vachtsevanos, Yan Wang, Wei He, Marcos E. Orchard, Jun Zhou, Guanfeng Liu and Xiaolong Li. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Knowledge and Data Engineering, Knowledge-Based Systems, Information Sciences and Journal of Agricultural and Food Chemistry.
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.