Bin Cui

13.3k citations
368 papers · 7.8k indexed · 4 hit papers · h-index 44

Impact in

Papers in

Bin Cui

334 papers receiving 7.6k citations

Hit Papers

Diffusion Models: A Comprehensive Survey of Methods and Applications 2023 · 694 citations
6942013202620172021200400600

Peers

Bin Cui
Comparison fields: 5 of 179
  • Information Systems 3.0k
  • Artificial Intelligence 3.9k
  • Signal Processing 1.1k
  • Transportation 682
  • Computer Vision and Pattern Recognition 2.0k
Replace Kotagiri Ramamohanarao with:
Kotagiri Ramamohanarao Australia
Ji-Rong Wen China
Yannis Manolopoulos Greece
Hanghang Tong United States
Tao Li United States
Yizhou Sun United States
Xia Hu United States
Kian‐Lee Tan Singapore
Ling Liu United States
Wenwu Zhu China
Bin Cui relative to Kotagiri Ramamohanarao Australia Kotagiri Ramamohanarao's profile →
Citations per field
00.5×4.1×
Kotagiri Ramamohanarao · 1×
Citations per year

Countries citing papers authored by Bin Cui

Since Specialization
Citations

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

Fields of papers citing papers by Bin Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Bin Cui, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bin Cui Line = papers co-authored together Bin Cui links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
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18 20206
19 2016170
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Real Time Simulation of Large Scale Water Surface Based On GPU
20091

About Bin Cui

Bin Cui is a scholar working on Signal Processing, Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition and Information Systems, having authored 368 papers that have together received 7.8k indexed citations. Recurring topics across this work include Data Management and Algorithms (56 papers), Advanced Graph Neural Networks (53 papers), Caching and Content Delivery (44 papers), Advanced Database Systems and Queries (44 papers), Data Stream Mining Techniques (44 papers), Recommender Systems and Techniques (43 papers), Complex Network Analysis Techniques (29 papers) and Graph Theory and Algorithms (28 papers). The work is most often cited by research in Information Systems (3.0k citations), Artificial Intelligence (3.9k citations), Signal Processing (1.1k citations), Transportation (682 citations) and Computer Vision and Pattern Recognition (2.0k citations). Bin Cui has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Hongzhi Yin, Wentao Zhang, Yingxia Shao, Shiwen Wu, Fei Sun, Jiawei Jiang, Zhiting Hu, Ling Chen, Junjie Yao and X. H. Xie. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment, ACM Transactions on Information Systems, The VLDB Journal and World Wide Web.

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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