Yiheng Shu
About
In The Last Decade
Yiheng Shu
3 papers receiving 134 citations
Peers
Comparison fields: 5 of 26
- Information Systems 118
- Artificial Intelligence 92
- Management Science and Operations Research 34
- Computer Vision and Pattern Recognition 28
- Computer Networks and Communications 13
Countries citing papers authored by Yiheng Shu
This map shows the geographic impact of Yiheng Shu'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 Yiheng Shu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yiheng Shu more than expected).
Fields of papers citing papers by Yiheng Shu
This network shows the impact of papers produced by Yiheng Shu. 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 Yiheng Shu. The network helps show where Yiheng Shu may publish in the future.
Co-authorship network of co-authors of Yiheng Shu
This figure shows the co-authorship network connecting the top 25 collaborators of Yiheng Shu. A scholar is included among the top collaborators of Yiheng Shu 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 Yiheng Shu. Yiheng Shu 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 | 138 | |
| 3 | Deep Learning-based Sequential Recommender Systems: Concepts, Algorithms, and Evaluations | 1 |
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.