Ge Yu
- Hardware and Architecture top 1%
- Parallel Computing and Optimization Techniques 33
- Signal Processing top 1%
- Data Management and Algorithms 79
- Artificial Intelligence top 0.5%
- Advanced Graph Neural Networks 41
- Privacy-Preserving Technologies in Data 25
-
- Advanced Database Systems and Queries 37
- Information Systems top 1%
- Cloud Computing and Resource Management 33
-
- Graph Theory and Algorithms 42
- Advanced Image and Video Retrieval Techniques 27
- Journals
- Frontiers of Computer Science (16 papers)IEEE Transactions on Knowledge and Data Engineering (16 papers)Proceedings of the VLDB Endowment (14 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Ge Yu
341 papers receiving 3.6k citations
Peers
Comparison fields: 5 of 141
- Hardware and Architecture 660
- Signal Processing 641
- Artificial Intelligence 1.6k
- Computer Networks and Communications 1.1k
- Information Systems 721
Countries citing papers authored by Ge Yu
This map shows the geographic impact of Ge Yu'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 Ge Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ge Yu more than expected).
Fields of papers citing papers by Ge Yu
This network shows the impact of papers produced by Ge Yu. 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 Ge Yu. The network helps show where Ge Yu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ge Yu, 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 | 2 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 0 | |
| 10 | 2023 | 8 | |
| 11 | 2023 | 17 | |
| 12 | 2018 | 56 | |
| 13 | 2018 | 5 | |
| 14 | Application of fuzzy PID control in intelligent street light control system | 2018 | 2 |
| 15 | 2013 | 6 | |
| 16 | Optimal k-constraint coverage queries on spatial objects | 2012 | 1 |
| 17 | Enhancing Keyword Search in Relational Databases Using Nearly Duplicate Records. | 2010 | 3 |
| 18 | 2009 | 5 | |
| 19 | 2007 | 2 | |
| 20 | M + -tree: a new dynamical multidimensional index for metric spaces | 2003 | 22 |
About Ge Yu
Ge Yu is a scholar working on Signal Processing, Hardware and Architecture and Artificial Intelligence, having authored 380 papers that have together received 3.8k indexed citations. Recurring topics across this work include Data Management and Algorithms (79 papers), Graph Theory and Algorithms (42 papers), Advanced Graph Neural Networks (41 papers), Advanced Database Systems and Queries (37 papers), Parallel Computing and Optimization Techniques (33 papers), Cloud Computing and Resource Management (33 papers), Advanced Image and Video Retrieval Techniques (27 papers) and Privacy-Preserving Technologies in Data (25 papers). The work is most often cited by research in Hardware and Architecture (660 citations), Signal Processing (641 citations) and Artificial Intelligence (1.6k citations). Ge Yu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Nan Guan, Wang Yi, Yu Gu, Martin Stigge, Yanfeng Zhang, Guoren Wang, Yin Yang, Xiaokui Xiao, Jia Xu and Daling Wang. Their work appears in journals such as Frontiers of Computer Science, IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment, World Wide Web and IEEE Access.
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.