Pan Hui

21.3k total citations · 10 hit papers
388 papers, 13.8k citations indexed

About

Pan Hui is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Pan Hui has authored 388 papers receiving a total of 13.8k indexed citations (citations by other indexed papers that have themselves been cited), including 201 papers in Computer Networks and Communications, 72 papers in Computer Vision and Pattern Recognition and 70 papers in Information Systems. Recurrent topics in Pan Hui's work include Opportunistic and Delay-Tolerant Networks (107 papers), Caching and Content Delivery (88 papers) and IoT and Edge/Fog Computing (67 papers). Pan Hui is often cited by papers focused on Opportunistic and Delay-Tolerant Networks (107 papers), Caching and Content Delivery (88 papers) and IoT and Edge/Fog Computing (67 papers). Pan Hui collaborates with scholars based in Hong Kong, Finland and China. Pan Hui's co-authors include Jon Crowcroft, Eiko Yoneki, Christophe Diot, Augustin Chaintreau, James Scott, Yong Li, Sokol Kosta, Carlos Bermejo, Depeng Jin and Richard Gass and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Automatic Control and Proceedings of the IEEE.

In The Last Decade

Pan Hui

370 papers receiving 13.3k citations

Hit Papers

BUBBLE Rap: Social-Based ... 2005 2026 2012 2019 2011 2012 2007 2005 2008 250 500 750 1000

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Pan Hui 9.4k 2.9k 2.2k 1.6k 1.5k 388 13.8k
Cecilia Mascolo 4.4k 0.5× 1.6k 0.6× 1.1k 0.5× 2.5k 1.5× 1.5k 1.0× 271 9.8k
Jon Crowcroft 17.6k 1.9× 5.6k 2.0× 2.8k 1.3× 1.4k 0.9× 1.1k 0.7× 527 22.4k
David Kotz 6.2k 0.7× 2.0k 0.7× 1.6k 0.7× 1.0k 0.6× 1.6k 1.0× 295 9.8k
Sajal K. Das 15.4k 1.6× 8.6k 3.0× 2.0k 0.9× 917 0.6× 2.5k 1.6× 911 21.4k
Ramesh Govindan 24.0k 2.5× 9.1k 3.1× 1.6k 0.7× 671 0.4× 2.6k 1.7× 338 28.1k
Mirco Musolesi 2.9k 0.3× 1.2k 0.4× 617 0.3× 1.7k 1.1× 1.3k 0.8× 153 7.6k
Zhiwen Yu 2.2k 0.2× 1.9k 0.7× 1.7k 0.8× 2.1k 1.3× 2.6k 1.7× 520 9.2k
Lionel M. Ni 10.7k 1.1× 10.6k 3.7× 1.4k 0.6× 1.2k 0.8× 3.5k 2.2× 450 22.0k
Tarek Abdelzaher 13.3k 1.4× 6.3k 2.2× 2.3k 1.1× 1.0k 0.6× 2.1k 1.4× 468 19.4k
Yu Wang 6.6k 0.7× 4.8k 1.7× 1.2k 0.6× 893 0.6× 2.0k 1.3× 633 13.6k

Countries citing papers authored by Pan Hui

Since Specialization
Citations

This map shows the geographic impact of Pan Hui'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 Pan Hui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pan Hui more than expected).

Fields of papers citing papers by Pan Hui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pan Hui. 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 Pan Hui. The network helps show where Pan Hui may publish in the future.

Co-authorship network of co-authors of Pan Hui

This figure shows the co-authorship network connecting the top 25 collaborators of Pan Hui. A scholar is included among the top collaborators of Pan Hui based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pan Hui. Pan Hui is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hui, Pan, et al.. (2025). Framing metaverse identity: A multidimensional framework for governing digital selves. Telecommunications Policy. 49(3). 102906–102906. 2 indexed citations
2.
Lu, Xiaofeng, et al.. (2025). EARVP: Efficient Aggregation for Federated Learning With Robustness, Verifiability, and Privacy. IEEE Transactions on Information Forensics and Security. 20. 5936–5951.
3.
Wang, Yuyang, et al.. (2024). Using a virtual reality interview simulator to explore factors influencing people’s behavior. Virtual Reality. 28(1). 6 indexed citations
4.
Hui, Pan, et al.. (2024). AI Robustness Against Attacks in City-Scale Autonomous Drone Deployments. Computer. 57(12). 47–57.
5.
Lu, Xiaofeng, et al.. (2024). Self-simulation and Meta-Model Aggregation Based Heterogeneous Graph Coupled Federated Learning. IEEE Internet of Things Journal. 1–1. 3 indexed citations
6.
Tarkoma, Sasu, Pan Hui, Hyowon Lee, et al.. (2023). The Price is Right? The Economic Value of Sharing Sensors. IEEE Transactions on Computational Social Systems. 11(3). 3468–3482.
7.
Zhou, Pengyuan, Lik‐Hang Lee, Abbas Mehrabi, et al.. (2022). Federated split GANs for collaborative training with heterogeneous devices. Software Impacts. 14. 100436–100436. 1 indexed citations
8.
Li, Tong, Xia Tong, Huandong Wang, et al.. (2022). Smartphone App Usage Analysis: Datasets, Methods, and Applications. IEEE Communications Surveys & Tutorials. 24(2). 937–966. 84 indexed citations
9.
Motlagh, Naser Hossein, Xiang Su, Sasu Tarkoma, et al.. (2022). Toward City-Scale Litter Monitoring Using Autonomous Ground Vehicles. IEEE Pervasive Computing. 21(3). 74–83. 8 indexed citations
10.
Xu, Dianlei, Tong Li, Yong Li, et al.. (2021). Edge Intelligence: Empowering Intelligence to the Edge of Network. Proceedings of the IEEE. 109(11). 1778–1837. 139 indexed citations
11.
Li, Tong, Mingyang Zhang, Yong Li, et al.. (2021). The Impact of Covid-19 on Smartphone Usage. IEEE Internet of Things Journal. 8(23). 16723–16733. 32 indexed citations
12.
Li, Tong, Yong Li, Mohammad A. Hoque, et al.. (2020). To What Extent We Repeat Ourselves? Discovering Daily Activity Patterns Across Mobile App Usage. IEEE Transactions on Mobile Computing. 21(4). 1492–1507. 69 indexed citations
13.
Lu, Xiaofeng, et al.. (2020). Privacy-Preserving Asynchronous Federated Learning Mechanism for Edge Network Computing. IEEE Access. 8. 48970–48981. 107 indexed citations
14.
Lu, Xiaofeng, Xiao Zhou, Meng Wan, Píetro Lió, & Pan Hui. (2020). Domain-Oriented Topic Discovery Based on Features Extraction and Topic Clustering. IEEE Access. 8. 93648–93662. 6 indexed citations
15.
Lu, Xiaofeng, et al.. (2020). Continuous authentication by free-text keystroke based on CNN and RNN. Computers & Security. 96. 101861–101861. 39 indexed citations
16.
Zhang, Mingyang, Tong Li, Yue Yu, et al.. (2020). Urban Anomaly Analytics: Description, Detection, and Prediction. IEEE Transactions on Big Data. 8(3). 809–826. 64 indexed citations
17.
Xu, Dianlei, Amit Samanta, Yong Li, et al.. (2019). Network Coding For Data Delivery in Caching at Edge: Concept, Model, and Algorithms. IEEE Transactions on Vehicular Technology. 68(10). 10066–10080. 13 indexed citations
18.
Entezari‐Maleki, Reza, et al.. (2019). Performance Evaluation of Epidemic Content Retrieval in DTNs With Restricted Mobility. IEEE Transactions on Network and Service Management. 16(2). 701–714. 9 indexed citations
19.
Gao, Hui, Chi Harold Liu, Jian Tang, et al.. (2018). Online Quality-Aware Incentive Mechanism for Mobile Crowd Sensing with Extra Bonus. IEEE Transactions on Mobile Computing. 18(11). 2589–2603. 64 indexed citations
20.
Xu, Dianlei, Yong Li, Xinlei Chen, et al.. (2018). A Survey of Opportunistic Offloading. IEEE Communications Surveys & Tutorials. 20(3). 2198–2236. 109 indexed citations

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.

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