Ran Zhao
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Molecular Biology
- Control and Systems Engineering
- Social Psychology
- Co-authors
- Tiancheng ZhaoMaxine EskénaziJustine CassellDong Hwan LeeDaniel SidobreChun‐yang ZhangYoichi MatsuyamaHong Kyu Lee
- Topics
- Robotic Path Planning Algorithms (11 papers)Optical measurement and interference techniques (9 papers)Image Processing Techniques and Applications (6 papers)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Ran Zhao
38 papers receiving 704 citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Artificial Intelligence 458
- Computer Vision and Pattern Recognition 237
- Molecular Biology 66
- Control and Systems Engineering 58
- Social Psychology 51
Countries citing papers authored by Ran Zhao
This map shows the geographic impact of Ran Zhao'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 Ran Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ran Zhao more than expected).
Fields of papers citing papers by Ran Zhao
This network shows the impact of papers produced by Ran Zhao. 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 Ran Zhao. The network helps show where Ran Zhao may publish in the future.
Co-authorship network of co-authors of Ran Zhao
This figure shows the co-authorship network connecting the top 25 collaborators of Ran Zhao. A scholar is included among the top collaborators of Ran Zhao 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 Ran Zhao. Ran Zhao 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 | 1 | |
| 3 | 6 | |
| 4 | 1 | |
| 5 | 17 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | 40 | |
| 10 | 21 | |
| 11 | 4 | |
| 12 | 21 | |
| 13 | Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencodersbreakdown → | 406 |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 2 | |
| 17 | 17 | |
| 18 | 15 | |
| 19 | 5 | |
| 20 | On Parameter Selection for Reducing Premature Convergence of Genetic Algorithms. | 3 |
About Ran Zhao
Ran Zhao is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Control and Systems Engineering, having authored 40 papers that have together received 736 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (11 papers), Optical measurement and interference techniques (9 papers) and Image Processing Techniques and Applications (6 papers). The work is most often cited by research in Artificial Intelligence (458 citations), Computer Vision and Pattern Recognition (237 citations) and Media Technology (31 citations). Ran Zhao has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Tiancheng Zhao, Maxine Eskénazi, Justine Cassell, Dong Hwan Lee, Daniel Sidobre, Chun‐yang Zhang, Yoichi Matsuyama, Hong Kyu Lee, Sushma A. Akoju and Shili Zhao. Their work appears in journals such as Analytical Chemistry, Chemical Engineering Journal and Tetrahedron.
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.