Nan Cao
Impact in
- Computational Mathematics top 2%
-
- Data Visualization and Analytics
- Video Analysis and Summarization
Papers in
-
- Data Visualization and Analytics 83
- Video Analysis and Summarization 26
- Journals
- IEEE Transactions on Visualization and Computer Graphics (36 papers)Proceedings of the ACM on Human-Computer Interaction (3 papers)Data Mining and Knowledge Discovery (3 papers)IEEE Transactions on Knowledge and Data Engineering (3 papers)Computer Graphics Forum (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Nan Cao
147 papers receiving 3.5k citations
Peers
Comparison fields: 5 of 158
- Computational Mathematics 66
- Computer Vision and Pattern Recognition 2.0k
- Statistical and Nonlinear Physics 549
- Artificial Intelligence 1.4k
- Signal Processing 449
Countries citing papers authored by Nan Cao
This map shows the geographic impact of Nan Cao'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 Nan Cao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nan Cao more than expected).
Fields of papers citing papers by Nan Cao
This network shows the impact of papers produced by Nan Cao. 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 Nan Cao. The network helps show where Nan Cao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nan Cao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 6 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 2 | |
| 8 | 2023 | 4 | |
| 9 | 2022 | 4 | |
| 10 | 2022 | 13 | |
| 11 | 2020 | 3 | |
| 12 | 2019 | 6 | |
| 13 | 2019 | 1 | |
| 14 | 2019 | 13 | |
| 15 | 2019 | 5 | |
| 16 | 2016 | 9 | |
| 17 | 2015 | 26 | |
| 18 | 2014 | 46 | |
| 19 | 2012 | 131 | |
| 20 | 2011 | 100 |
About Nan Cao
Nan Cao is a scholar working on Computer Vision and Pattern Recognition, Computational Mathematics, Statistical and Nonlinear Physics, Human-Computer Interaction and Artificial Intelligence, having authored 155 papers that have together received 3.6k indexed citations. Recurring topics across this work include Data Visualization and Analytics (83 papers), Complex Network Analysis Techniques (35 papers), Video Analysis and Summarization (26 papers), Multimedia Communication and Technology (18 papers), Advanced Text Analysis Techniques (16 papers), Anomaly Detection Techniques and Applications (14 papers), Time Series Analysis and Forecasting (10 papers) and Innovative Human-Technology Interaction (10 papers). The work is most often cited by research in Computational Mathematics (66 citations), Computer Vision and Pattern Recognition (2.0k citations), Statistical and Nonlinear Physics (549 citations), Artificial Intelligence (1.4k citations) and Signal Processing (449 citations). Nan Cao has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include David Gotz, Yu‐Ru Lin, Yang Shi, Jimeng Sun, Shi‐Xia Liu, Huamin Qu, Shunan Guo, Zhuochen Jin, Xingyu Lan and Hanghang Tong. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Proceedings of the ACM on Human-Computer Interaction, Data Mining and Knowledge Discovery, IEEE Transactions on Knowledge and Data Engineering and Computer Graphics Forum.
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.