David A. Shamma
- Computer Vision and Pattern Recognition top 0.1%
- Artificial Intelligence top 0.2%
- Sociology and Political Science top 2%
- Statistical and Nonlinear Physics top 2%
- Information Systems top 2%
- Co-authors
- Li-Jia LiMichael S. BernsteinLi Fei-FeiRanjay KrishnaYannis KalantidisStephanie ChenOliver GrothKenji Hata
- Topics
- Video Analysis and Summarization (21 papers)Advanced Image and Video Retrieval Techniques (14 papers)Innovative Human-Technology Interaction (14 papers)
- Journals
- Communications of the ACMInternational Journal of Computer VisionIEEE Computer Graphics and Applications
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
David A. Shamma
93 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Computer Vision and Pattern Recognition 4.3k
- Artificial Intelligence 3.0k
- Sociology and Political Science 698
- Statistical and Nonlinear Physics 359
- Information Systems 358
Countries citing papers authored by David A. Shamma
This map shows the geographic impact of David A. Shamma'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 David A. Shamma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David A. Shamma more than expected).
Fields of papers citing papers by David A. Shamma
This network shows the impact of papers produced by David A. Shamma. 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 David A. Shamma. The network helps show where David A. Shamma may publish in the future.
Co-authorship network of co-authors of David A. Shamma
This figure shows the co-authorship network connecting the top 25 collaborators of David A. Shamma. A scholar is included among the top collaborators of David A. Shamma 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 David A. Shamma. David A. Shamma 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 | 2 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 17 | |
| 8 | 21 | |
| 9 | 3 | |
| 10 | Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition | 1 |
| 11 | 5 | |
| 12 | 19 | |
| 13 | 5 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 15 | |
| 18 | 25 | |
| 19 | 0 | |
| 20 | Teaching the Foundations in AI: Mobile Robots and Symbolic Victories | 4 |
About David A. Shamma
David A. Shamma is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 101 papers that have together received 6.2k indexed citations. Recurring topics across this work include Video Analysis and Summarization (21 papers), Advanced Image and Video Retrieval Techniques (14 papers) and Innovative Human-Technology Interaction (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (4.3k citations), Artificial Intelligence (3.0k citations) and Human-Computer Interaction (299 citations). David A. Shamma has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Li-Jia Li, Michael S. Bernstein, Li Fei-Fei, Ranjay Krishna, Yannis Kalantidis, Stephanie Chen, Oliver Groth, Kenji Hata, Yuke Zhu and Justin Johnson. Their work appears in journals such as Communications of the ACM, International Journal of Computer Vision and IEEE Computer Graphics and Applications.
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.