Hongyu Li
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Atmospheric Science
- Information Systems
- Co-authors
- Lin ZhangJunyu NiuElizabeth C. MinorXiuju LiuSteven M. ColmanErik T. BrownYing ShenJianwei Lu
- Topics
- Adversarial Robustness in Machine Learning (4 papers)Privacy-Preserving Technologies in Data (4 papers)Neural Networks and Applications (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceNutrientsIEEE Transactions on Fuzzy Systems
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Hongyu Li
20 papers receiving 336 citations
Peers
Comparison fields: 5 of 82
- Signal Processing 149
- Computer Vision and Pattern Recognition 133
- Artificial Intelligence 69
- Atmospheric Science 52
- Information Systems 34
Countries citing papers authored by Hongyu Li
This map shows the geographic impact of Hongyu Li'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 Hongyu Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongyu Li more than expected).
Fields of papers citing papers by Hongyu Li
This network shows the impact of papers produced by Hongyu Li. 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 Hongyu Li. The network helps show where Hongyu Li may publish in the future.
Co-authorship network of co-authors of Hongyu Li
This figure shows the co-authorship network connecting the top 25 collaborators of Hongyu Li. A scholar is included among the top collaborators of Hongyu Li 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 Hongyu Li. Hongyu Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 5 | |
| 14 | 29 | |
| 15 | 1 | |
| 16 | Nonlinear Dynamic Analysis Efficiency by Using a GPU Parallelization | 1 |
| 17 | 50 | |
| 18 | 90 | |
| 19 | 19 | |
| 20 | Supervised local tangent space alignment for classification | 3 |
About Hongyu Li
Hongyu Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 23 papers that have together received 342 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Privacy-Preserving Technologies in Data (4 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Signal Processing (149 citations), Computer Vision and Pattern Recognition (133 citations) and Earth-Surface Processes (22 citations). Hongyu Li has collaborated with scholars based in China, United States and France. Frequent co-authors include Lin Zhang, Junyu Niu, Elizabeth C. Minor, Xiuju Liu, Steven M. Colman, Erik T. Brown, Ying Shen, Jianwei Lu, Wen‐Cheng Chen and Xiaolin Li. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Nutrients and IEEE Transactions on Fuzzy Systems.
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.