Cong Guo
Impact in
- Computational Mathematics top 10%
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
Papers in
-
- Stochastic Gradient Optimization Techniques 3
-
- Advanced Neural Network Applications 8
- Co-authors
- Jingwen Leng (13 shared papers)Ji He (5 shared papers)Yunxin Liu (4 shared papers)Minyi Guo (9 shared papers)Ashraf Aboulnaga (1 shared paper)Chen Zhang (3 shared papers)Yuhao Zhu (4 shared papers)Libo Zhang (6 shared papers)
- Journals
- Composite Structures (4 papers)IEEE Transactions on Computers (2 papers)Radiation Measurements (1 paper)Information Sciences (1 paper)Frontiers of Physics (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Cong Guo
45 papers receiving 488 citations
Peers
Comparison fields: 5 of 90
- Computational Mathematics 15
- Hardware and Architecture 64
- Computer Vision and Pattern Recognition 159
- Modeling and Simulation 22
- Statistical and Nonlinear Physics 58
Countries citing papers authored by Cong Guo
This map shows the geographic impact of Cong Guo'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 Cong Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cong Guo more than expected).
Fields of papers citing papers by Cong Guo
This network shows the impact of papers produced by Cong Guo. 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 Cong Guo. The network helps show where Cong Guo may publish in the future.
Co-authors
The 25 scholars most cited alongside Cong Guo, 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 64 | |
| 2 | 2013 | 52 | |
| 3 | 2022 | 50 | |
| 4 | 2020 | 36 | |
| 5 | 2022 | 27 | |
| 6 | 2014 | 27 | |
| 7 | 2020 | 26 | |
| 8 | 2022 | 21 | |
| 9 | 2020 | 17 | |
| 10 | 2023 | 15 | |
| 11 | 2021 | 14 | |
| 12 | 2021 | 14 | |
| 13 | 2014 | 13 | |
| 14 | 2024 | 11 | |
| 15 | 2014 | 11 | |
| 16 | 2024 | 10 | |
| 17 | 2024 | 10 | |
| 18 | 2024 | 9 | |
| 19 | 2022 | 9 | |
| 20 | 2024 | 7 |
About Cong Guo
Cong Guo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Hardware and Architecture and Computer Networks and Communications, having authored 53 papers that have together received 499 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Parallel Computing and Optimization Techniques (6 papers), Advanced Memory and Neural Computing (4 papers), Security in Wireless Sensor Networks (4 papers), Advanced Authentication Protocols Security (3 papers), Stochastic Gradient Optimization Techniques (3 papers), Tensor decomposition and applications (3 papers) and Mechanical Behavior of Composites (3 papers). The work is most often cited by research in Computational Mathematics (15 citations), Hardware and Architecture (64 citations), Computer Vision and Pattern Recognition (159 citations), Modeling and Simulation (22 citations) and Statistical and Nonlinear Physics (58 citations). Cong Guo has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jingwen Leng, Ji He, Yunxin Liu, Minyi Guo, Ashraf Aboulnaga, Chen Zhang, Yuhao Zhu, Libo Zhang, Yang Wang and Zhiqiang Xie. Their work appears in journals such as Composite Structures, IEEE Transactions on Computers, Radiation Measurements, Information Sciences and Frontiers of Physics.
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.