Bin Qian
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- Explainable Artificial Intelligence (XAI)
- Machine Learning in Healthcare
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
Papers in
-
- IoT and Edge/Fog Computing 6
- Caching and Content Delivery 1
-
- Privacy-Preserving Technologies in Data 3
- Data Stream Mining Techniques 2
- Co-authors
- Rajiv Ranjan (9 shared papers)Zhenyu Wen (9 shared papers)Omer Rana (4 shared papers)Graham Morgan (2 shared papers)Tejal Shah (2 shared papers)Pankesh Patel (1 shared paper)Rudresh Dwivedi (1 shared paper)Devam Dave (1 shared paper)
- Journals
- ACM Computing Surveys (3 papers)IEEE Network (2 papers)IEEE Transactions on Services Computing (1 paper)Sensors (1 paper)IEEE Transactions on Cognitive Communications and Networking (1 paper)
- Partner nations
- ChinaUnited KingdomAustralia
In The Last Decade
Bin Qian
12 papers receiving 698 citations
Bin Qian's Hit Papers
Peers
Comparison fields: 5 of 119
- Health Informatics 55
- Artificial Intelligence 327
- Health Information Management 29
- Computer Networks and Communications 121
- Computer Vision and Pattern Recognition 95
Countries citing papers authored by Bin Qian
This map shows the geographic impact of Bin Qian'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 Bin Qian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Qian more than expected).
Fields of papers citing papers by Bin Qian
This network shows the impact of papers produced by Bin Qian. 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 Bin Qian. The network helps show where Bin Qian may publish in the future.
Co-authors
The 25 scholars most cited alongside Bin Qian, 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 | Explainable AI (XAI): Core Ideas, Techniques, and Solutions Hit paper breakdown → | 2022 | 506 |
| 2 | 2020 | 108 | |
| 3 | 2021 | 34 | |
| 4 | A Review on Edge Large Language Models: Design, Execution, and Applications Hit paper breakdown → | 2025 | 22 |
| 5 | 2022 | 19 | |
| 6 | 2022 | 10 | |
| 7 | 2023 | 9 | |
| 8 | 2024 | 6 | |
| 9 | 1985 | 5 | |
| 10 | 2022 | 4 | |
| 11 | Orchestrating Development Lifecycle of Machine Learning Based IoT Applications: A Survey. | 2019 | 1 |
| 12 | 2025 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2025 | 0 | |
| 15 | 2019 | 0 |
About Bin Qian
Bin Qian is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems and Aerospace Engineering, having authored 15 papers that have together received 725 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (6 papers), Cloud Computing and Resource Management (3 papers), Privacy-Preserving Technologies in Data (3 papers), Advanced Neural Network Applications (2 papers), Data Stream Mining Techniques (2 papers), Image and Video Quality Assessment (2 papers), Caching and Content Delivery (1 paper) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Health Informatics (55 citations), Artificial Intelligence (327 citations), Health Information Management (29 citations), Computer Networks and Communications (121 citations) and Computer Vision and Pattern Recognition (95 citations). Bin Qian has collaborated with scholars based in China, United Kingdom and Australia. Frequent co-authors include Rajiv Ranjan, Zhenyu Wen, Omer Rana, Graham Morgan, Tejal Shah, Pankesh Patel, Rudresh Dwivedi, Devam Dave, Albert Y. Zomaya and Renyu Yang. Their work appears in journals such as ACM Computing Surveys, IEEE Network, IEEE Transactions on Services Computing, Sensors and IEEE Transactions on Cognitive Communications and Networking.
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.