Ziheng Duan
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Molecular Biology
- Computer Vision and Pattern Recognition
- Building and Construction
- Topics
- Single-cell and spatial transcriptomics (8 papers)Advanced Graph Neural Networks (6 papers)Time Series Analysis and Forecasting (5 papers)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Ziheng Duan
22 papers receiving 280 citations
Peers
Comparison fields: 5 of 82
- Artificial Intelligence 127
- Signal Processing 72
- Molecular Biology 58
- Computer Vision and Pattern Recognition 25
- Building and Construction 22
Countries citing papers authored by Ziheng Duan
This map shows the geographic impact of Ziheng Duan'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 Ziheng Duan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ziheng Duan more than expected).
Fields of papers citing papers by Ziheng Duan
This network shows the impact of papers produced by Ziheng Duan. 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 Ziheng Duan. The network helps show where Ziheng Duan may publish in the future.
Co-authorship network of co-authors of Ziheng Duan
This figure shows the co-authorship network connecting the top 25 collaborators of Ziheng Duan. A scholar is included among the top collaborators of Ziheng Duan 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 Ziheng Duan. Ziheng Duan 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 | 4 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 1 | |
| 10 | 8 | |
| 11 | 4 | |
| 12 | 54 | |
| 13 | 31 | |
| 14 | 36 | |
| 15 | Modeling Complex Spatial Patterns with Temporal Features via Heterogenous Graph Embedding Networks. | 1 |
| 16 | Hierarchical and Fast Graph Similarity Computation via Graph Coarsening and Deep Graph Learning. | 2 |
| 17 | Multivariate Time Series Forecasting Based on Causal Inference with Transfer Entropy and Graph Neural Network. | 11 |
| 18 | 32 | |
| 19 | 5 | |
| 20 | 12 |
About Ziheng Duan
Ziheng Duan is a scholar working on Signal Processing, Artificial Intelligence and General Social Sciences, having authored 23 papers that have together received 285 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (8 papers), Advanced Graph Neural Networks (6 papers) and Time Series Analysis and Forecasting (5 papers). The work is most often cited by research in Signal Processing (72 citations), Artificial Intelligence (127 citations) and Statistical and Nonlinear Physics (21 citations). Ziheng Duan has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Yueyang Wang, Haoyan Xu, Yida Huang, Jie Feng, Zhongbin Xu, Yizhou Sun, Wei Wang, Yueting Zhuang, Fei Wu and Che-Yu Lee. Their work appears in journals such as Bioinformatics, International Journal of Molecular Sciences and PLoS Computational Biology.
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.