Ruizhou Ding
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Computer Networks and Communications
- Signal Processing
- Co-authors
- Diana MarculescuTing-Wu ChinR.D. BlantonZhuo ChenBodhi PriyanthaDi WangDimitrios LymberopoulosJie Liu
- Topics
- Advanced Neural Network Applications (11 papers)Machine Learning and Data Classification (5 papers)Adversarial Robustness in Machine Learning (4 papers)
- Journals
- ACM Transactions on Embedded Computing SystemsACM Transactions on Reconfigurable Technology and SystemsarXiv (Cornell University)
- Partner nations
- United StatesChina
In The Last Decade
Ruizhou Ding
12 papers receiving 227 citations
Peers
Comparison fields: 5 of 46
- Computer Vision and Pattern Recognition 159
- Artificial Intelligence 142
- Electrical and Electronic Engineering 49
- Computer Networks and Communications 19
- Signal Processing 11
Countries citing papers authored by Ruizhou Ding
This map shows the geographic impact of Ruizhou Ding'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 Ruizhou Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruizhou Ding more than expected).
Fields of papers citing papers by Ruizhou Ding
This network shows the impact of papers produced by Ruizhou Ding. 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 Ruizhou Ding. The network helps show where Ruizhou Ding may publish in the future.
Co-authorship network of co-authors of Ruizhou Ding
This figure shows the co-authorship network connecting the top 25 collaborators of Ruizhou Ding. A scholar is included among the top collaborators of Ruizhou Ding based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ruizhou Ding. Ruizhou Ding is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | LeGR: Filter Pruning via Learned Global Ranking. | 10 |
| 4 | AdaScale: Towards Real-time Video Object Detection Using Adaptive Scaling | 7 |
| 5 | 27 | |
| 6 | 12 | |
| 7 | 86 | |
| 8 | 18 | |
| 9 | 33 | |
| 10 | 9 | |
| 11 | 1 | |
| 12 | 20 |
About Ruizhou Ding
Ruizhou Ding is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Environmental Engineering, having authored 12 papers that have together received 231 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (11 papers), Machine Learning and Data Classification (5 papers) and Adversarial Robustness in Machine Learning (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (159 citations), Artificial Intelligence (142 citations) and Neurology (11 citations). Ruizhou Ding has collaborated with scholars based in United States and China. Frequent co-authors include Diana Marculescu, Ting-Wu Chin, R.D. Blanton, Zhuo Chen, Bodhi Priyantha, Di Wang, Dimitrios Lymberopoulos, Jie Liu, Dimitrios Stamoulis and Rongye Shi. Their work appears in journals such as ACM Transactions on Embedded Computing Systems, ACM Transactions on Reconfigurable Technology and Systems and arXiv (Cornell University).
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.