Ge Yu
Impact in
- Hardware and Architecture top 1%
- Real-Time Systems Scheduling
- Embedded Systems Design Techniques
- Parallel Computing and Optimization Techniques
- Signal Processing top 1%
- Data Management and Algorithms
Papers in
-
- Advanced Graph Neural Networks 41
-
- Advanced Database Systems and Queries 37
- Co-authors
- Nan Guan (20 shared papers)Wang Yi (12 shared papers)Yu Gu (73 shared papers)Yanfeng Zhang (34 shared papers)Martin Stigge (4 shared papers)Guoren Wang (21 shared papers)Yin Yang (4 shared papers)Xiaokui Xiao (4 shared papers)
- Journals
- Frontiers of Computer Science (16 papers)IEEE Transactions on Knowledge and Data Engineering (16 papers)Proceedings of the VLDB Endowment (14 papers)World Wide Web (12 papers)IEEE Access (10 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-authors
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
Showing the 20 most-cited of 380 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 140 | |
| 2 | 2019 | 131 | |
| 3 | 2009 | 122 | |
| 4 | 2013 | 94 | |
| 5 | 2009 | 81 | |
| 6 | 2012 | 79 | |
| 7 | 2010 | 74 | |
| 8 | 2001 | 73 | |
| 9 | 2017 | 67 | |
| 10 | 2010 | 63 | |
| 11 | 2018 | 56 | |
| 12 | 2021 | 52 | |
| 13 | 2016 | 51 | |
| 14 | 2008 | 49 | |
| 15 | 2010 | 49 | |
| 16 | 2019 | 45 | |
| 17 | 2011 | 42 | |
| 18 | 2015 | 41 | |
| 19 | 2020 | 39 | |
| 20 | 2010 | 38 |
About Ge Yu
Ge Yu is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Signal Processing and Computer Vision and Pattern Recognition, 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 Real-Time Systems Scheduling (25 papers). The work is most often cited by research in Hardware and Architecture (660 citations), Signal Processing (641 citations), Artificial Intelligence (1.6k citations), Computer Networks and Communications (1.1k citations) and Information Systems (721 citations). Ge Yu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Nan Guan, Wang Yi, Yu Gu, Yanfeng Zhang, Martin Stigge, 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.