Guoping Long
Impact in
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
- Computational Mathematics top 5%
Papers in
-
- Parallel Computing and Optimization Techniques 17
- Embedded Systems Design Techniques 4
-
- Advanced Data Storage Technologies 9
- Distributed and Parallel Computing Systems 5
- Co-authors
- Yunquan Zhang (8 shared papers)Shengen Yan (5 shared papers)Wei Lin (4 shared papers)Chuan Wu (4 shared papers)Zhen Zheng (3 shared papers)Shiqing Fan (2 shared papers)Dongrui Fan (8 shared papers)Shuzi Niu (4 shared papers)
- Journals
- ACM SIGPLAN Notices (2 papers)Lecture notes in computer science (10 papers)Machine Learning (1 paper)Journal of Computer Science and Technology (3 papers)Chinese Journal of Computers (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Guoping Long
39 papers receiving 551 citations
Peers
Comparison fields: 5 of 55
- Hardware and Architecture 247
- Computational Mathematics 18
- Computer Vision and Pattern Recognition 189
- Computer Networks and Communications 207
- Artificial Intelligence 236
Countries citing papers authored by Guoping Long
This map shows the geographic impact of Guoping Long'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 Guoping Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guoping Long more than expected).
Fields of papers citing papers by Guoping Long
This network shows the impact of papers produced by Guoping Long. 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 Guoping Long. The network helps show where Guoping Long may publish in the future.
Co-authors
The 25 scholars most cited alongside Guoping Long, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 121 | |
| 2 | 2017 | 67 | |
| 3 | 2013 | 65 | |
| 4 | 2022 | 46 | |
| 5 | 2009 | 31 | |
| 6 | 2013 | 21 | |
| 7 | 2012 | 21 | |
| 8 | 2010 | 21 | |
| 9 | 2020 | 21 | |
| 10 | 2013 | 16 | |
| 11 | 2020 | 15 | |
| 12 | 2022 | 13 | |
| 13 | 2013 | 11 | |
| 14 | Online Bayesian max-margin subspace multi-view learning | 2016 | 10 |
| 15 | 2011 | 9 | |
| 16 | 2016 | 7 | |
| 17 | 2016 | 6 | |
| 18 | 2019 | 6 | |
| 19 | 2008 | 6 | |
| 20 | 2016 | 6 |
About Guoping Long
Guoping Long is a scholar working on Hardware and Architecture, Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 39 papers that have together received 570 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (17 papers), Advanced Data Storage Technologies (9 papers), Advanced Neural Network Applications (6 papers), Advanced Image and Video Retrieval Techniques (5 papers), Distributed and Parallel Computing Systems (5 papers), Embedded Systems Design Techniques (4 papers), Stochastic Gradient Optimization Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Hardware and Architecture (247 citations), Computational Mathematics (18 citations), Computer Vision and Pattern Recognition (189 citations), Computer Networks and Communications (207 citations) and Artificial Intelligence (236 citations). Guoping Long has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yunquan Zhang, Shengen Yan, Wei Lin, Chuan Wu, Zhen Zheng, Shiqing Fan, Dongrui Fan, Shuzi Niu, Jun Yang and Lixue Xia. Their work appears in journals such as ACM SIGPLAN Notices, Lecture notes in computer science, Machine Learning, Journal of Computer Science and Technology and Chinese Journal of Computers.
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.