Pian Qi
Impact in
- Artificial Intelligence top 10%
- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Anomaly Detection Techniques and Applications
- Stochastic Gradient Optimization Techniques
Papers in
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- Privacy-Preserving Technologies in Data 4
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- Vehicular Ad Hoc Networks (VANETs) 1
- IoT Networks and Protocols 1
- Co-authors
- Diletta Chiaro (10 shared papers)Francesco Piccialli (10 shared papers)Michele Ianni (1 shared paper)Antonella Guzzo (1 shared paper)Giancarlo Fortino (1 shared paper)Fabio Giampaolo (2 shared papers)Chun Liu (1 shared paper)Stefano Izzo (2 shared papers)
In The Last Decade
Pian Qi
11 papers receiving 326 citations
Pian Qi's Hit Papers
Peers
Comparison fields: 5 of 69
- Health Informatics 10
- Artificial Intelligence 200
- Computer Networks and Communications 69
- Computer Science Applications 14
- Information Systems 50
Countries citing papers authored by Pian Qi
This map shows the geographic impact of Pian Qi'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 Pian Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pian Qi more than expected).
Fields of papers citing papers by Pian Qi
This network shows the impact of papers produced by Pian Qi. 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 Pian Qi. The network helps show where Pian Qi may publish in the future.
Co-authors
The 12 scholars most cited alongside Pian Qi, 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 | Model aggregation techniques in federated learning: A comprehensive survey Hit paper breakdown → | 2023 | 167 |
| 2 | 2023 | 53 | |
| 3 | 2023 | 38 | |
| 4 | 2022 | 23 | |
| 5 | 2024 | 22 | |
| 6 | 2022 | 17 | |
| 7 | 2024 | 6 | |
| 8 | 2025 | 5 | |
| 9 | 2024 | 3 | |
| 10 | 2025 | 3 | |
| 11 | 2024 | 3 | |
| 12 | 2025 | 0 |
About Pian Qi
Pian Qi is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Control and Systems Engineering, Information Systems and Statistical and Nonlinear Physics, having authored 12 papers that have together received 340 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (4 papers), Blockchain Technology Applications and Security (2 papers), Digital Transformation in Industry (2 papers), Traffic Prediction and Management Techniques (2 papers), Traffic control and management (2 papers), Model Reduction and Neural Networks (2 papers), Vehicular Ad Hoc Networks (VANETs) (1 paper) and IoT Networks and Protocols (1 paper). The work is most often cited by research in Health Informatics (10 citations), Artificial Intelligence (200 citations), Computer Networks and Communications (69 citations), Computer Science Applications (14 citations) and Information Systems (50 citations). Pian Qi has collaborated with scholars based in Italy and China. Frequent co-authors include Diletta Chiaro, Francesco Piccialli, Michele Ianni, Antonella Guzzo, Giancarlo Fortino, Fabio Giampaolo, Chun Liu, Stefano Izzo, Salvatore Cuomo and Valerio Bellandi. Their work appears in journals such as Information Fusion, Expert Systems with Applications, IEEE Transactions on Industrial Informatics, Future Generation Computer Systems and Information Sciences.
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.