Ping Xiong
-
- Mobile Crowdsensing and Crowdsourcing 17
- Artificial Intelligence top 2%
- Privacy-Preserving Technologies in Data 37
- Cryptography and Data Security 12
- Information Systems top 5%
- Recommender Systems and Techniques 5
-
- Neural Networks Stability and Synchronization 6
-
- Privacy, Security, and Data Protection 14
-
- Transportation Planning and Optimization 6
-
- Nuclear Engineering Thermal-Hydraulics 5
Ping Xiong
93 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 130
- Computer Science Applications 113
- Artificial Intelligence 535
- Biological Psychiatry 25
- Information Systems 198
- Computer Networks and Communications 195
Countries citing papers authored by Ping Xiong
This map shows the geographic impact of Ping Xiong'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 Ping Xiong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ping Xiong more than expected).
Fields of papers citing papers by Ping Xiong
This network shows the impact of papers produced by Ping Xiong. 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 Ping Xiong. The network helps show where Ping Xiong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ping Xiong, 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 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 18 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 7 | |
| 10 | 2023 | 1 | |
| 11 | 2023 | 5 | |
| 12 | 2020 | 11 | |
| 13 | 2018 | 14 | |
| 14 | 2018 | 32 | |
| 15 | Disturbance attenuation to T-S fuzzy model of Lurie system under actuator saturation | 2012 | 0 |
| 16 | The analysis of operating principle and performance of EMCCD | 2009 | 1 |
| 17 | Study on Park-and-Ride Selection Behaviors during Large Special Events based on Travel Time | 2009 | 2 |
| 18 | Analysis of Transport Planning and Implementation Effect of EXPO 2005 Aichi Japan | 2006 | 0 |
| 19 | Method of weighting ordering based on rough sets and its application | 2005 | 0 |
| 20 | AN ALGORITHM OF MINING FUZZY ASSOCIATE RULES | 2005 | 1 |
About Ping Xiong
Ping Xiong is a scholar working on Computer Science Applications, Artificial Intelligence and Transportation, having authored 106 papers that have together received 1.2k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (37 papers), Mobile Crowdsensing and Crowdsourcing (17 papers), Privacy, Security, and Data Protection (14 papers), Cryptography and Data Security (12 papers), Neural Networks Stability and Synchronization (6 papers), Transportation Planning and Optimization (6 papers), Recommender Systems and Techniques (5 papers) and Nuclear Engineering Thermal-Hydraulics (5 papers). The work is most often cited by research in Computer Science Applications (113 citations), Artificial Intelligence (535 citations) and Biological Psychiatry (25 citations). Ping Xiong has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Tianqing Zhu, Wanlei Zhou, Lefeng Zhang, Gang Li, Philip S. Yu, Tao Lu, Yongli Ren, Jianjun Tu, Tao Zhang and Xiaofeng Wang. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Future Generation Computer Systems, Knowledge and Information Systems, IEEE Transactions on Information Forensics and Security and Computers & Security.
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.